R-universe search: dissimilarity

vegandevs

vegan:Community Ecology Package

Ordination methods, diversity analysis and other functions for community and vegetation ecologists.

Maintained by Jari Oksanen. Last updated 16 days ago.

ecological-modelling ecology ordination fortran openblas

23.0 match 472 stars 19.41 score 15k scripts 440 dependents

blasbenito

distantia:Advanced Toolset for Efficient Time Series Dissimilarity Analysis

Fast C++ implementation of Dynamic Time Warping for time series dissimilarity analysis, with applications in environmental monitoring and sensor data analysis, climate science, signal processing and pattern recognition, and financial data analysis. Built upon the ideas presented in Benito and Birks (2020) <doi:10.1111/ecog.04895>, provides tools for analyzing time series of varying lengths and structures, including irregular multivariate time series. Key features include individual variable contribution analysis, restricted permutation tests for statistical significance, and imputation of missing data via GAMs. Additionally, the package provides an ample set of tools to prepare and manage time series data.

Maintained by Blas M. Benito. Last updated 25 days ago.

55.7 match 23 stars 5.76 score 11 scripts

fitzlab-al

gdm:Generalized Dissimilarity Modeling

A toolkit with functions to fit, plot, summarize, and apply Generalized Dissimilarity Models. Mokany K, Ware C, Woolley SNC, Ferrier S, Fitzpatrick MC (2022) <doi:10.1111/geb.13459> Ferrier S, Manion G, Elith J, Richardson K (2007) <doi:10.1111/j.1472-4642.2007.00341.x>.

Maintained by Matt Fitzpatrick. Last updated 2 months ago.

cpp

22.3 match 35 stars 8.12 score 145 scripts

gavinsimpson

analogue:Analogue and Weighted Averaging Methods for Palaeoecology

Fits Modern Analogue Technique and Weighted Averaging transfer function models for prediction of environmental data from species data, and related methods used in palaeoecology.

Maintained by Gavin L. Simpson. Last updated 6 months ago.

20.0 match 14 stars 8.96 score 185 scripts 4 dependents

pmontman

TSclust:Time Series Clustering Utilities

A set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.

Maintained by Pablo Montero Manso. Last updated 5 years ago.

27.8 match 2 stars 5.76 score 170 scripts 8 dependents

l-ramirez-lopez

resemble:Memory-Based Learning in Spectral Chemometrics

Functions for dissimilarity analysis and memory-based learning (MBL, a.k.a local modeling) in complex spectral data sets. Most of these functions are based on the methods presented in Ramirez-Lopez et al. (2013) <doi:10.1016/j.geoderma.2012.12.014>.

Maintained by Leonardo Ramirez-Lopez. Last updated 2 years ago.

chemoinformatics chemometrics infrared-spectroscopy lazy-learning local-regression machine-learning memory-based-learning nir pedometrics soil-spectroscopy spectral-data spectral-library spectroscopy openblas cpp openmp

23.4 match 20 stars 5.91 score 27 scripts

bioc

goSorensen:Statistical inference based on the Sorensen-Dice dissimilarity and the Gene Ontology (GO)

This package implements inferential methods to compare gene lists in terms of their biological meaning as expressed in the GO. The compared gene lists are characterized by cross-tabulation frequency tables of enriched GO items. Dissimilarity between gene lists is evaluated using the Sorensen-Dice index. The fundamental guiding principle is that two gene lists are taken as similar if they share a great proportion of common enriched GO items.

Maintained by Pablo Flores. Last updated 5 months ago.

annotation go genesetenrichment software microarray pathways geneexpression multiplecomparison graphandnetwork reactome clustering kegg

27.4 match 4.56 score 12 scripts

phiala

ecodist:Dissimilarity-Based Functions for Ecological Analysis

Dissimilarity-based analysis functions including ordination and Mantel test functions, intended for use with spatial and community ecological data. The original package description is in Goslee and Urban (2007) <doi:10.18637/jss.v022.i07>, with further statistical detail in Goslee (2010) <doi:10.1007/s11258-009-9641-0>.

Maintained by Sarah Goslee. Last updated 1 years ago.

openblas

12.5 match 9 stars 9.84 score 566 scripts 9 dependents

traminer

TraMineR:Trajectory Miner: a Sequence Analysis Toolkit

Set of sequence analysis tools for manipulating, describing and rendering categorical sequences, and more generally mining sequence data in the field of social sciences. Although this sequence analysis package is primarily intended for state or event sequences that describe time use or life courses such as family formation histories or professional careers, its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for converting sequences from one format to another. It offers several functions for describing and rendering sequences, for computing distances between sequences with different metrics (among which optimal matching), original dissimilarity-based analysis tools, and functions for extracting the most frequent event subsequences and identifying the most discriminating ones among them. A user's guide can be found on the TraMineR web page.

Maintained by Gilbert Ritschard. Last updated 3 months ago.

cpp

14.0 match 11 stars 8.24 score 534 scripts 13 dependents

kurthornik

clue:Cluster Ensembles

CLUster Ensembles.

Maintained by Kurt Hornik. Last updated 4 months ago.

11.0 match 2 stars 9.85 score 496 scripts 401 dependents

pavel-fibich

gawdis:Multi-Trait Dissimilarity with more Uniform Contributions

R function gawdis() produces multi-trait dissimilarity with more uniform contributions of different traits. de Bello et al. (2021) <doi:10.1111/2041-210X.13537> presented the approach based on minimizing the differences in the correlation between the dissimilarity of each trait, or groups of traits, and the multi-trait dissimilarity. This is done using either an analytic or a numerical solution, both available in the function.

Maintained by Pavel Fibich. Last updated 2 years ago.

20.6 match 5 stars 5.20 score 21 scripts 1 dependents

cran

TSdist:Distance Measures for Time Series Data

A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series. U. Mori, A. Mendiburu and J.A. Lozano (2016), <doi:10.32614/RJ-2016-058>.

Maintained by Usue Mori. Last updated 3 years ago.

27.6 match 5 stars 3.85 score 94 scripts 5 dependents

cran

betapart:Partitioning Beta Diversity into Turnover and Nestedness Components

Functions to compute pair-wise dissimilarities (distance matrices) and multiple-site dissimilarities, separating the turnover and nestedness-resultant components of taxonomic (incidence and abundance based), functional and phylogenetic beta diversity.

Maintained by Andres Baselga. Last updated 2 years ago.

26.2 match 2 stars 3.97 score 6 dependents

plangfelder

WGCNA:Weighted Correlation Network Analysis

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.

Maintained by Peter Langfelder. Last updated 6 months ago.

cpp

10.8 match 54 stars 9.65 score 5.3k scripts 32 dependents

biorgeo

bioregion:Comparison of Bioregionalisation Methods

The main purpose of this package is to propose a transparent methodological framework to compare bioregionalisation methods based on hierarchical and non-hierarchical clustering algorithms (Kreft & Jetz (2010) <doi:10.1111/j.1365-2699.2010.02375.x>) and network algorithms (Lenormand et al. (2019) <doi:10.1002/ece3.4718> and Leroy et al. (2019) <doi:10.1111/jbi.13674>).

Maintained by Maxime Lenormand. Last updated 10 days ago.

biogeography bioregion bioregionalization cpp

16.1 match 7 stars 6.27 score 11 scripts

hpetren

chemodiv:Analysing Chemodiversity of Phytochemical Data

Quantify and visualise various measures of chemical diversity and dissimilarity, for phytochemical compounds and other sets of chemical composition data. Importantly, these measures can incorporate biosynthetic and/or structural properties of the chemical compounds, resulting in a more comprehensive quantification of diversity and dissimilarity. For details, see Petrén, Köllner and Junker (2023) <doi:10.1111/nph.18685>.

Maintained by Hampus Petrén. Last updated 2 years ago.

22.0 match 5 stars 4.57 score 15 scripts

mhahsler

seriation:Infrastructure for Ordering Objects Using Seriation

Infrastructure for ordering objects with an implementation of several seriation/sequencing/ordination techniques to reorder matrices, dissimilarity matrices, and dendrograms. Also provides (optimally) reordered heatmaps, color images and clustering visualizations like dissimilarity plots, and visual assessment of cluster tendency plots (VAT and iVAT). Hahsler et al (2008) <doi:10.18637/jss.v025.i03>.

Maintained by Michael Hahsler. Last updated 3 months ago.

combinatorial-optimization ordination seriation fortran

6.7 match 77 stars 14.07 score 640 scripts 79 dependents

bioc

mina:Microbial community dIversity and Network Analysis

An increasing number of microbiome datasets have been generated and analyzed with the help of rapidly developing sequencing technologies. At present, analysis of taxonomic profiling data is mainly conducted using composition-based methods, which ignores interactions between community members. Besides this, a lack of efficient ways to compare microbial interaction networks limited the study of community dynamics. To better understand how community diversity is affected by complex interactions between its members, we developed a framework (Microbial community dIversity and Network Analysis, mina), a comprehensive framework for microbial community diversity analysis and network comparison. By defining and integrating network-derived community features, we greatly reduce noise-to-signal ratio for diversity analyses. A bootstrap and permutation-based method was implemented to assess community network dissimilarities and extract discriminative features in a statistically principled way.

Maintained by Rui Guan. Last updated 5 months ago.

software workflowstep cpp

19.5 match 5 stars 4.85 score 14 scripts

mmaechler

cluster:"Finding Groups in Data": Cluster Analysis Extended Rousseeuw et al.

Methods for Cluster analysis. Much extended the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) "Finding Groups in Data".

Maintained by Martin Maechler. Last updated 4 days ago.

7.6 match 3 stars 11.98 score 14k scripts 2.2k dependents

trinker

qdap:Bridging the Gap Between Qualitative Data and Quantitative Analysis

Automates many of the tasks associated with quantitative discourse analysis of transcripts containing discourse including frequency counts of sentence types, words, sentences, turns of talk, syllables and other assorted analysis tasks. The package provides parsing tools for preparing transcript data. Many functions enable the user to aggregate data by any number of grouping variables, providing analysis and seamless integration with other R packages that undertake higher level analysis and visualization of text. This affords the user a more efficient and targeted analysis. 'qdap' is designed for transcript analysis, however, many functions are applicable to other areas of Text Mining/ Natural Language Processing.

Maintained by Tyler Rinker. Last updated 4 years ago.

qdap quantitative-discourse-analysis text-analysis text-mining text-plotting openjdk

7.3 match 176 stars 9.61 score 1.3k scripts 3 dependents

jarioksa

natto:An Extreme 'vegan' Package of Experimental Code

Random code that is too experimental or too weird to be included in the vegan package.

Maintained by Jari Oksanen. Last updated 28 days ago.

14.6 match 8 stars 4.68 score 1 scripts

pmair78

smacof:Multidimensional Scaling

Implements the following approaches for multidimensional scaling (MDS) based on stress minimization using majorization (smacof): ratio/interval/ordinal/spline MDS on symmetric dissimilarity matrices, MDS with external constraints on the configuration, individual differences scaling (idioscal, indscal), MDS with spherical restrictions, and ratio/interval/ordinal/spline unfolding (circular restrictions, row-conditional). Various tools and extensions like jackknife MDS, bootstrap MDS, permutation tests, MDS biplots, gravity models, unidimensional scaling, drift vectors (asymmetric MDS), classical scaling, and Procrustes are implemented as well.

Maintained by Patrick Mair. Last updated 5 months ago.

8.6 match 5 stars 7.86 score 152 scripts 24 dependents

mhahsler

arules:Mining Association Rules and Frequent Itemsets

Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides C implementations of the association mining algorithms Apriori and Eclat. Hahsler, Gruen and Hornik (2005) <doi:10.18637/jss.v014.i15>.

Maintained by Michael Hahsler. Last updated 1 months ago.

arules association-rules frequent-itemsets

4.8 match 194 stars 13.99 score 3.3k scripts 28 dependents

dvrbts

labdsv:Ordination and Multivariate Analysis for Ecology

A variety of ordination and community analyses useful in analysis of data sets in community ecology. Includes many of the common ordination methods, with graphical routines to facilitate their interpretation, as well as several novel analyses.

Maintained by David W. Roberts. Last updated 2 years ago.

fortran

9.6 match 3 stars 6.08 score 452 scripts 13 dependents

grahamjwhite

IndexNumR:Index Number Calculation

Computes bilateral and multilateral index numbers. It has support for many standard bilateral indexes as well as multilateral index number methods such as GEKS, GEKS-Tornqvist (or CCDI), Geary-Khamis and the weighted time product dummy (for details on these methods see Diewert and Fox (2020) <doi:10.1080/07350015.2020.1816176>). It also supports updating of multilateral indexes using several splicing methods.

Maintained by Graham White. Last updated 1 years ago.

index-numbers

8.5 match 15 stars 6.20 score 71 scripts 1 dependents

mhahsler

recommenderlab:Lab for Developing and Testing Recommender Algorithms

Provides a research infrastructure to develop and evaluate collaborative filtering recommender algorithms. This includes a sparse representation for user-item matrices, many popular algorithms, top-N recommendations, and cross-validation. Hahsler (2022) <doi:10.48550/arXiv.2205.12371>.

Maintained by Michael Hahsler. Last updated 7 months ago.

collaborative-filtering recommender-system

4.8 match 214 stars 10.07 score 840 scripts 2 dependents

pvermees

provenance:Statistical Toolbox for Sedimentary Provenance Analysis

Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, principal component analysis, correspondence analysis, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov-Smirnov, Kuiper, Wasserstein-2 or Sircombe-Hazelton L2 distances. Categorical provenance proxies such as chemical compositions are compared with the Aitchison and Bray-Curtis distances,and count data with the chi-square distance. Varietal data can either be converted to one or more distributional datasets, or directly compared using the multivariate Wasserstein distance. Also included are tools to plot compositional and count data on ternary diagrams and point-counting data on radial plots, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.

Maintained by Pieter Vermeesch. Last updated 2 months ago.

8.4 match 14 stars 5.52 score 79 scripts 1 dependents

sandrinepavoine

adiv:Analysis of Diversity

Functions, data sets and examples for the calculation of various indices of biodiversity including species, functional and phylogenetic diversity. Part of the indices are expressed in terms of equivalent numbers of species. The package also provides ways to partition biodiversity across spatial or temporal scales (alpha, beta, gamma diversities). In addition to the quantification of biodiversity, ordination approaches are available which rely on diversity indices and allow the detailed identification of species, functional or phylogenetic differences between communities.

Maintained by Sandrine Pavoine. Last updated 1 years ago.

20.4 match 1 stars 2.28 score 63 scripts

sergioventurini

dmbc:Model Based Clustering of Binary Dissimilarity Measurements

Functions for fitting a Bayesian model for grouping binary dissimilarity matrices in homogeneous clusters. Currently, it includes methods only for binary data (<doi:10.18637/jss.v100.i16>).

Maintained by Sergio Venturini. Last updated 6 months ago.

openblas cpp openmp

14.0 match 2 stars 3.30 score 4 scripts

emf-creaf

vegclust:Fuzzy Clustering of Vegetation Data

A set of functions to: (1) perform fuzzy clustering of vegetation data (De Caceres et al, 2010) <doi:10.1111/j.1654-1103.2010.01211.x>; (2) to assess ecological community similarity on the basis of structure and composition (De Caceres et al, 2013) <doi:10.1111/2041-210X.12116>.

Maintained by Miquel De Cáceres. Last updated 8 months ago.

7.1 match 2 stars 6.28 score 52 scripts 6 dependents

markmfredrickson

optmatch:Functions for Optimal Matching

Distance based bipartite matching using minimum cost flow, oriented to matching of treatment and control groups in observational studies ('Hansen' and 'Klopfer' 2006 <doi:10.1198/106186006X137047>). Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.

Maintained by Josh Errickson. Last updated 3 months ago.

matching openblas cpp

3.6 match 47 stars 12.22 score 588 scripts 5 dependents

hannameyer

CAST:'caret' Applications for Spatial-Temporal Models

Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>; Milà et al. (2022) <doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>; Linnenbrink et al. (2023) <doi:10.5194/egusphere-2023-1308>; Schumacher et al. (2024) <doi:10.5194/egusphere-2024-2730>. The package is described in detail in Meyer et al. (2024) <doi:10.48550/arXiv.2404.06978>.

Maintained by Hanna Meyer. Last updated 2 months ago.

autocorrelation caret feature-selection machine-learning overfitting predictive-modeling spatial spatio-temporal variable-selection

3.5 match 114 stars 11.97 score 298 scripts 1 dependents

mlampros

ClusterR:Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering

Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, <doi:10.18637/jss.v001.i04>; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, <doi:10.1145/1772690.1772862>; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, <doi:10.21105/joss.00026>; (iv) "Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, <doi:10.1126/science.1136800>.

Maintained by Lampros Mouselimis. Last updated 9 months ago.

affinity-propagation cpp11 gmm kmeans kmedoids-clustering mini-batch-kmeans rcpparmadillo openblas cpp openmp

3.6 match 84 stars 11.08 score 640 scripts 24 dependents

anttonalberdi

hilldiv:Integral Analysis of Diversity Based on Hill Numbers

Tools for analysing, comparing, visualising and partitioning diversity based on Hill numbers. 'hilldiv' is an R package that provides a set of functions to assist analysis of diversity for diet reconstruction, microbial community profiling or more general ecosystem characterisation analyses based on Hill numbers, using OTU/ASV tables and associated phylogenetic trees as inputs. The package includes functions for (phylo)diversity measurement, (phylo)diversity profile plotting, (phylo)diversity comparison between samples and groups, (phylo)diversity partitioning and (dis)similarity measurement. All of these grounded in abundance-based and incidence-based Hill numbers. The statistical framework developed around Hill numbers encompasses many of the most broadly employed diversity (e.g. richness, Shannon index, Simpson index), phylogenetic diversity (e.g. Faith's PD, Allen's H, Rao's quadratic entropy) and dissimilarity (e.g. Sorensen index, Unifrac distances) metrics. This enables the most common analyses of diversity to be performed while grounded in a single statistical framework. The methods are described in Jost et al. (2007) <DOI:10.1890/06-1736.1>, Chao et al. (2010) <DOI:10.1098/rstb.2010.0272> and Chiu et al. (2014) <DOI:10.1890/12-0960.1>; and reviewed in the framework of molecularly characterised biological systems in Alberdi & Gilbert (2019) <DOI:10.1111/1755-0998.13014>.

Maintained by Antton Alberdi. Last updated 4 years ago.

9.0 match 11 stars 4.35 score 41 scripts

jacekbialek

PriceIndices:Calculating Bilateral and Multilateral Price Indexes

Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020) <doi:10.1080/07350015.2020.1816176>, Białek (2019) <doi:10.2478/jos-2019-0014> or Białek (2020) <doi:10.2478/jos-2020-0037>.

Maintained by Jacek Białek. Last updated 2 months ago.

6.4 match 11 stars 6.06 score 16 scripts

topepo

caret:Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Maintained by Max Kuhn. Last updated 3 months ago.

2.0 match 1.6k stars 19.24 score 61k scripts 303 dependents

grunwaldlab

poppr:Genetic Analysis of Populations with Mixed Reproduction

Population genetic analyses for hierarchical analysis of partially clonal populations built upon the architecture of the 'adegenet' package. Originally described in Kamvar, Tabima, and Grünwald (2014) <doi:10.7717/peerj.281> with version 2.0 described in Kamvar, Brooks, and Grünwald (2015) <doi:10.3389/fgene.2015.00208>.

Maintained by Zhian N. Kamvar. Last updated 10 months ago.

clonality genetic-analysis genetic-distances minimum-spanning-networks multilocus-genotypes multilocus-lineages population-genetics populations openmp

3.5 match 69 stars 10.84 score 672 scripts

elbersb

segregation:Entropy-Based Segregation Indices

Computes segregation indices, including the Index of Dissimilarity, as well as the information-theoretic indices developed by Theil (1971) <isbn:978-0471858454>, namely the Mutual Information Index (M) and Theil's Information Index (H). The M, further described by Mora and Ruiz-Castillo (2011) <doi:10.1111/j.1467-9531.2011.01237.x> and Frankel and Volij (2011) <doi:10.1016/j.jet.2010.10.008>, is a measure of segregation that is highly decomposable. The package provides tools to decompose the index by units and groups (local segregation), and by within and between terms. The package also provides a method to decompose differences in segregation as described by Elbers (2021) <doi:10.1177/0049124121986204>. The package includes standard error estimation by bootstrapping, which also corrects for small sample bias. The package also contains functions for visualizing segregation patterns.

Maintained by Benjamin Elbers. Last updated 1 years ago.

entropy segregation statistics cpp

5.5 match 36 stars 6.44 score 51 scripts

matthewkling

phylospatial:Spatial Phylogenetic Analysis

Conduct various analyses on spatial phylogenetics. Use your data on an evolutionary tree and geographic distributions of the terminal taxa to compute diversity and endemism metrics, test significance with null model randomization, analyze community turnover and biotic regionalization, and perform spatial conservation prioritizations. All functions support quantitative community data in addition to binary data.

Maintained by Matthew Kling. Last updated 4 days ago.

5.8 match 6 stars 6.16 score 9 scripts

leondap

recluster:Ordination Methods for the Analysis of Beta-Diversity Indices

The analysis of different aspects of biodiversity requires specific algorithms. For example, in regionalisation analyses, the high frequency of ties and zero values in dissimilarity matrices produced by Beta-diversity turnover produces hierarchical cluster dendrograms whose topology and bootstrap supports are affected by the order of rows in the original matrix. Moreover, visualisation of biogeographical regionalisation can be facilitated by a combination of hierarchical clustering and multi-dimensional scaling. The recluster package provides robust techniques to visualise and analyse pattern of biodiversity and to improve occurrence data for cryptic taxa.

Maintained by Leonardo Dapporto. Last updated 4 months ago.

7.3 match 4 stars 4.69 score 41 scripts

chrhennig

fpc:Flexible Procedures for Clustering

Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Standardisation of cluster validation statistics by random clusterings and comparison between many clustering methods and numbers of clusters based on this. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc.

Maintained by Christian Hennig. Last updated 6 months ago.

3.6 match 11 stars 9.25 score 2.6k scripts 70 dependents

r-spatial

spdep:Spatial Dependence: Weighting Schemes, Statistics

A collection of functions to create spatial weights matrix objects from polygon 'contiguities', from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial 'autocorrelation', including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunção/Reis' (1999) <doi:10.1002/(SICI)1097-0258(19990830)18:16%3C2147::AID-SIM179%3E3.0.CO;2-I> Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x> and multicoloured join count statistics, 'APLE' ('Li 'et al.' ) <doi:10.1111/j.1538-4632.2007.00708.x>, local 'Moran's I', 'Gearys C' ('Anselin' 1995) <doi:10.1111/j.1538-4632.1995.tb00338.x> and 'Getis/Ord' G ('Ord' and 'Getis' 1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>, 'saddlepoint' approximations ('Tiefelsdorf' 2002) <doi:10.1111/j.1538-4632.2002.tb01084.x> and exact tests for global and local 'Moran's I' ('Bivand et al.' 2009) <doi:10.1016/j.csda.2008.07.021> and 'LOSH' local indicators of spatial heteroscedasticity ('Ord' and 'Getis') <doi:10.1007/s00168-011-0492-y>. The implementation of most of these measures is described in 'Bivand' and 'Wong' (2018) <doi:10.1007/s11749-018-0599-x>, with further extensions in 'Bivand' (2022) <doi:10.1111/gean.12319>. 'Lagrange' multiplier tests for spatial dependence in linear models are provided ('Anselin et al'. 1996) <doi:10.1016/0166-0462(95)02111-6>, as are 'Rao' score tests for hypothesised spatial 'Durbin' models based on linear models ('Koley' and 'Bera' 2023) <doi:10.1080/17421772.2023.2256810>. A local indicators for categorical data (LICD) implementation based on 'Carrer et al.' (2021) <doi:10.1016/j.jas.2020.105306> and 'Bivand et al.' (2017) <doi:10.1016/j.spasta.2017.03.003> was added in 1.3-7. From 'spdep' and 'spatialreg' versions >= 1.2-1, the model fitting functions previously present in this package are defunct in 'spdep' and may be found in 'spatialreg'.

Maintained by Roger Bivand. Last updated 18 days ago.

spatial-autocorrelation spatial-dependence spatial-weights

2.0 match 131 stars 16.62 score 6.0k scripts 107 dependents

chrhennig

prabclus:Functions for Clustering and Testing of Presence-Absence, Abundance and Multilocus Genetic Data

Distance-based parametric bootstrap tests for clustering with spatial neighborhood information. Some distance measures, Clustering of presence-absence, abundance and multilocus genetic data for species delimitation, nearest neighbor based noise detection. Genetic distances between communities. Tests whether various distance-based regressions are equal. Try package?prabclus for on overview.

Maintained by Christian Hennig. Last updated 6 months ago.

5.4 match 1 stars 5.99 score 90 scripts 71 dependents

alarm-redist

redistmetrics:Redistricting Metrics

Reliable and flexible tools for scoring redistricting plans using common measures and metrics. These functions provide key direct access to tools useful for non-simulation analyses of redistricting plans, such as for measuring compactness or partisan fairness. Tools are designed to work with the 'redist' package seamlessly.

Maintained by Christopher T. Kenny. Last updated 9 months ago.

openblas cpp

4.0 match 10 stars 7.57 score 23 scripts 2 dependents

nceas

codyn:Community Dynamics Metrics

Univariate and multivariate temporal and spatial diversity indices, rank abundance curves, and community stability measures. The functions implement measures that are either explicitly temporal and include the option to calculate them over multiple replicates, or spatial and include the option to calculate them over multiple time points. Functions fall into five categories: static diversity indices, temporal diversity indices, spatial diversity indices, rank abundance curves, and community stability measures. The diversity indices are temporal and spatial analogs to traditional diversity indices. Specifically, the package includes functions to calculate community richness, evenness and diversity at a given point in space and time. In addition, it contains functions to calculate species turnover, mean rank shifts, and lags in community similarity between two time points. Details of the methods are available in Hallett et al. (2016) <doi:10.1111/2041-210X.12569> and Avolio et al. (2019) <doi:10.1002/ecs2.2881>.

Maintained by Matthew B. Jones. Last updated 4 years ago.

3.3 match 34 stars 9.07 score 230 scripts

adeverse

ade4:Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

Tools for multivariate data analysis. Several methods are provided for the analysis (i.e., ordination) of one-table (e.g., principal component analysis, correspondence analysis), two-table (e.g., coinertia analysis, redundancy analysis), three-table (e.g., RLQ analysis) and K-table (e.g., STATIS, multiple coinertia analysis). The philosophy of the package is described in Dray and Dufour (2007) <doi:10.18637/jss.v022.i04>.

Maintained by Aurélie Siberchicot. Last updated 12 days ago.

openblas cpp

2.0 match 39 stars 14.96 score 2.2k scripts 256 dependents

bioc

flowMatch:Matching and meta-clustering in flow cytometry

Matching cell populations and building meta-clusters and templates from a collection of FC samples.

Maintained by Ariful Azad. Last updated 5 months ago.

immunooncology clustering flowcytometry cpp

7.3 match 3.90 score 1 scripts

rekyt

funrar:Functional Rarity Indices Computation

Computes functional rarity indices as proposed by Violle et al. (2017) <doi:10.1016/j.tree.2017.02.002>. Various indices can be computed using both regional and local information. Functional Rarity combines both the functional aspect of rarity as well as the extent aspect of rarity. 'funrar' is presented in Grenié et al. (2017) <doi:10.1111/ddi.12629>.

Maintained by Matthias Grenié. Last updated 11 months ago.

ecological-models ecology rarity traits

3.6 match 17 stars 7.85 score 233 scripts 1 dependents

kit-iism-em

partitionComparison:Implements Measures for the Comparison of Two Partitions

Provides several measures ((dis)similarity, distance/metric, correlation, entropy) for comparing two partitions of the same set of objects. The different measures can be assigned to three different classes: Pair comparison (containing the famous Jaccard and Rand indices), set based, and information theory based. Many of the implemented measures can be found in Albatineh AN, Niewiadomska-Bugaj M and Mihalko D (2006) <doi:10.1007/s00357-006-0017-z> and Meila M (2007) <doi:10.1016/j.jmva.2006.11.013>. Partitions are represented by vectors of class labels which allow a straightforward integration with existing clustering algorithms (e.g. kmeans()). The package is mostly based on the S4 object system.

Maintained by Fabian Ball. Last updated 2 years ago.

comparison dissimilarity-measures distance-measures partitions similarity-measures

7.5 match 2 stars 3.78 score 60 scripts

bioc

phyloseq:Handling and analysis of high-throughput microbiome census data

phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.

Maintained by Paul J. McMurdie. Last updated 5 months ago.

immunooncology sequencing microbiome metagenomics clustering classification multiplecomparison geneticvariability

2.0 match 597 stars 13.90 score 8.4k scripts 37 dependents

tgouhier

biwavelet:Conduct Univariate and Bivariate Wavelet Analyses

This is a port of the WTC MATLAB package written by Aslak Grinsted and the wavelet program written by Christopher Torrence and Gibert P. Compo. This package can be used to perform univariate and bivariate (cross-wavelet, wavelet coherence, wavelet clustering) analyses.

Maintained by Tarik Gouhier. Last updated 7 months ago.

cpp

3.6 match 45 stars 7.51 score 81 scripts 1 dependents

sciviews

exploreit:Exploratory Data Analysis for 'SciViews::R'

Multivariate analysis and data exploration for the 'SciViews::R' dialect.

Maintained by Philippe Grosjean. Last updated 11 months ago.

multivariate-analysis sciviews statistical-methods

9.8 match 2.70 score 4 scripts

bioc

mia:Microbiome analysis

mia implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.

Maintained by Tuomas Borman. Last updated 2 days ago.

microbiome software dataimport analysis bioconductor

2.3 match 52 stars 11.50 score 316 scripts 5 dependents

bioc

SNPRelate:Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data

Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed an R package SNPRelate to provide a binary format for single-nucleotide polymorphism (SNP) data in GWAS utilizing CoreArray Genomic Data Structure (GDS) data files. The GDS format offers the efficient operations specifically designed for integers with two bits, since a SNP could occupy only two bits. SNPRelate is also designed to accelerate two key computations on SNP data using parallel computing for multi-core symmetric multiprocessing computer architectures: Principal Component Analysis (PCA) and relatedness analysis using Identity-By-Descent measures. The SNP GDS format is also used by the GWASTools package with the support of S4 classes and generic functions. The extended GDS format is implemented in the SeqArray package to support the storage of single nucleotide variations (SNVs), insertion/deletion polymorphism (indel) and structural variation calls in whole-genome and whole-exome variant data.

Maintained by Xiuwen Zheng. Last updated 5 months ago.

infrastructure genetics statisticalmethod principalcomponent bioinformatics gds-format pca simd snp openblas cpp

2.0 match 104 stars 12.69 score 1.6k scripts 18 dependents

loukiaspin

rnmamod:Bayesian Network Meta-Analysis with Missing Participants

A comprehensive suite of functions to perform and visualise pairwise and network meta-analysis with aggregate binary or continuous missing participant outcome data. The package covers core Bayesian one-stage models implemented in a systematic review with multiple interventions, including fixed-effect and random-effects network meta-analysis, meta-regression, evaluation of the consistency assumption via the node-splitting approach and the unrelated mean effects model (original and revised model proposed by Spineli, (2022) <doi:10.1177/0272989X211068005>), and sensitivity analysis (see Spineli et al., (2021) <doi:10.1186/s12916-021-02195-y>). Missing participant outcome data are addressed in all models of the package (see Spineli, (2019) <doi:10.1186/s12874-019-0731-y>, Spineli et al., (2019) <doi:10.1002/sim.8207>, Spineli, (2019) <doi:10.1016/j.jclinepi.2018.09.002>, and Spineli et al., (2021) <doi:10.1002/jrsm.1478>). The robustness to primary analysis results can also be investigated using a novel intuitive index (see Spineli et al., (2021) <doi:10.1177/0962280220983544>). Methods to evaluate the transitivity assumption quantitatively are provided (see Spineli, (2024) <doi:10.1186/s12874-024-02436-7>). A novel index to facilitate interpretation of local inconsistency is also available (see Spineli, (2024) <doi:0.1186/s13643-024-02680-4>) The package also offers a rich, user-friendly visualisation toolkit that aids in appraising and interpreting the results thoroughly and preparing the manuscript for journal submission. The visualisation tools comprise the network plot, forest plots, panel of diagnostic plots, heatmaps on the extent of missing participant outcome data in the network, league heatmaps on estimation and prediction, rankograms, Bland-Altman plot, leverage plot, deviance scatterplot, heatmap of robustness, barplot of Kullback-Leibler divergence, heatmap of comparison dissimilarities and dendrogram of comparison clustering. The package also allows the user to export the results to an Excel file at the working directory.

Maintained by Loukia Spineli. Last updated 9 days ago.

jags cpp

3.8 match 5 stars 6.64 score 12 scripts

a-s-melo

CommEcol:Community Ecology Analyses

Autosimilarity curves, standardization of spatial extent, dissimilarity indexes that overweight rare species, phylogenetic and functional (pairwise and multisample) dissimilarity indexes and nestedness for phylogenetic, functional and other diversity metrics. The methods for phylogenetic and functional nestedness is described in Melo, Cianciaruso and Almeida-Neto (2014) <doi:10.1111/2041-210X.12185>. This should be a complement to available packages, particularly 'vegan'.

Maintained by Adriano Sanches Melo. Last updated 9 months ago.

9.8 match 1 stars 2.39 score 41 scripts 1 dependents

idblr

ndi:Neighborhood Deprivation Indices

Computes various geospatial indices of socioeconomic deprivation and disparity in the United States. Some indices are considered "spatial" because they consider the values of neighboring (i.e., adjacent) census geographies in their computation, while other indices are "aspatial" because they only consider the value within each census geography. Two types of aspatial neighborhood deprivation indices (NDI) are available: including: (1) based on Messer et al. (2006) <doi:10.1007/s11524-006-9094-x> and (2) based on Andrews et al. (2020) <doi:10.1080/17445647.2020.1750066> and Slotman et al. (2022) <doi:10.1016/j.dib.2022.108002> who use variables chosen by Roux and Mair (2010) <doi:10.1111/j.1749-6632.2009.05333.x>. Both are a decomposition of multiple demographic characteristics from the U.S. Census Bureau American Community Survey 5-year estimates (ACS-5; 2006-2010 onward). Using data from the ACS-5 (2005-2009 onward), the package can also compute indices of racial or ethnic residential segregation, including but limited to those discussed in Massey & Denton (1988) <doi:10.1093/sf/67.2.281>, and additional indices of socioeconomic disparity.

Maintained by Ian D. Buller. Last updated 7 months ago.

census census-api census-data deprivation deprivation-stats disparity geospatial geospatial-data metric-development principal-component-analysis segregation-measures socio-economic-indicators

3.5 match 21 stars 6.67 score 7 scripts 1 dependents

skembel

picante:Integrating Phylogenies and Ecology

Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) <doi:10.1093/bioinformatics/btq166>.

Maintained by Steven W. Kembel. Last updated 2 years ago.

2.0 match 34 stars 11.42 score 1.1k scripts 16 dependents

ropensci

textreuse:Detect Text Reuse and Document Similarity

Tools for measuring similarity among documents and detecting passages which have been reused. Implements shingled n-gram, skip n-gram, and other tokenizers; similarity/dissimilarity functions; pairwise comparisons; minhash and locality sensitive hashing algorithms; and a version of the Smith-Waterman local alignment algorithm suitable for natural language.

Maintained by Yaoxiang Li. Last updated 30 days ago.

peer-reviewed cpp

2.4 match 200 stars 9.28 score 226 scripts

bioc

clusterSeq:Clustering of high-throughput sequencing data by identifying co-expression patterns

Identification of clusters of co-expressed genes based on their expression across multiple (replicated) biological samples.

Maintained by Samuel Granjeaud. Last updated 5 months ago.

sequencing differentialexpression multiplecomparison clustering geneexpression

5.1 match 4.26 score 2 scripts

pvermees

IsoplotR:Statistical Toolbox for Radiometric Geochronology

Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington', 'Ludwig' and Omnivariant Generalised Least-Squares ('OGLS') approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isochrons as well as 230Th-U evolution plots.

Maintained by Pieter Vermeesch. Last updated 1 months ago.

2.4 match 69 stars 9.08 score 95 scripts 6 dependents

nepem-ufsc

metan:Multi Environment Trials Analysis

Performs stability analysis of multi-environment trial data using parametric and non-parametric methods. Parametric methods includes Additive Main Effects and Multiplicative Interaction (AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>, Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>, geometric adaptability index by Mohammadi & Amri (2008) <doi:10.1007/s10681-007-9600-6>, joint regression analysis by Eberhart & Russel (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>, genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method, power law residuals (POLAR) statistics by Doring et al. (2015) <doi:10.1016/j.fcr.2015.08.005>, scale-adjusted coefficient of variation by Doring & Reckling (2018) <doi:10.1016/j.eja.2018.06.007>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, weighted average of absolute scores by Olivoto et al. (2019a) <doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>. Non-parametric methods includes superiority index by Lin & Binns (1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic stability by Huehn (1990) <doi:10.1007/BF00024241>, TOP third statistic by Fox et al. (1990) <doi:10.1007/BF00040364>. Functions for computing biometrical analysis such as path analysis, canonical correlation, partial correlation, clustering analysis, and tools for inspecting, manipulating, summarizing and plotting typical multi-environment trial data are also provided.

Maintained by Tiago Olivoto. Last updated 9 days ago.

2.3 match 2 stars 9.48 score 1.3k scripts 2 dependents

bioc

ChemmineR:Cheminformatics Toolkit for R

ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.

Maintained by Thomas Girke. Last updated 5 months ago.

cheminformatics biomedicalinformatics pharmacogenetics pharmacogenomics microtitreplateassay cellbasedassays visualization infrastructure dataimport clustering proteomics metabolomics cpp

2.3 match 14 stars 9.42 score 253 scripts 12 dependents

cran

Anthropometry:Statistical Methods for Anthropometric Data

Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.

Maintained by Guillermo Vinue. Last updated 2 years ago.

7.3 match 1 stars 2.78 score 2 dependents

mlampros

textTinyR:Text Processing for Small or Big Data Files

It offers functions for splitting, parsing, tokenizing and creating a vocabulary for big text data files. Moreover, it includes functions for building a document-term matrix and extracting information from those (term-associations, most frequent terms). It also embodies functions for calculating token statistics (collocations, look-up tables, string dissimilarities) and functions to work with sparse matrices. Lastly, it includes functions for Word Vector Representations (i.e. 'GloVe', 'fasttext') and incorporates functions for the calculation of (pairwise) text document dissimilarities. The source code is based on 'C++11' and exported in R through the 'Rcpp', 'RcppArmadillo' and 'BH' packages.

Maintained by Lampros Mouselimis. Last updated 1 years ago.

bh boost cpp11 processing rcpp rcpparmadillo text openblas cpp openmp

2.6 match 38 stars 7.64 score 244 scripts 1 dependents

adeverse

adespatial:Multivariate Multiscale Spatial Analysis

Tools for the multiscale spatial analysis of multivariate data. Several methods are based on the use of a spatial weighting matrix and its eigenvector decomposition (Moran's Eigenvectors Maps, MEM). Several approaches are described in the review Dray et al (2012) <doi:10.1890/11-1183.1>.

Maintained by Aurélie Siberchicot. Last updated 12 days ago.

openblas

1.8 match 36 stars 11.06 score 398 scripts 2 dependents

murphymv

dissCqN:Multiple Assemblage Dissimilarity for Orders q = 0-N

Calculate multiple or pairwise dissimilarity for orders q = 0-N (CqN; Chao et al., 2008 <doi:10/fcvn63>) for a set of species assemblages or interaction networks.

Maintained by Mark Murphy. Last updated 3 years ago.

5.4 match 3.70 score 2 scripts

biometry

bipartite:Visualising Bipartite Networks and Calculating Some (Ecological) Indices

Functions to visualise webs and calculate a series of indices commonly used to describe pattern in (ecological) webs. It focuses on webs consisting of only two levels (bipartite), e.g. pollination webs or predator-prey-webs. Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the web's topology.

Maintained by Carsten F. Dormann. Last updated 6 days ago.

cpp

1.8 match 37 stars 10.93 score 592 scripts 15 dependents

berchuck

womblR:Spatiotemporal Boundary Detection Model for Areal Unit Data

Implements a spatiotemporal boundary detection model with a dissimilarity metric for areal data with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC). The response variable can be modeled as Gaussian (no nugget), probit or Tobit link and spatial correlation is introduced at each time point through a conditional autoregressive (CAR) prior. Temporal correlation is introduced through a hierarchical structure and can be specified as exponential or first-order autoregressive. Full details of the package can be found in the accompanying vignette. Furthermore, the details of the package can be found in "Diagnosing Glaucoma Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method", by Berchuck et al (2018), <arXiv:1805.11636>. The paper is in press at the Journal of the American Statistical Association.

Maintained by Samuel I. Berchuck. Last updated 3 years ago.

openblas cpp

4.6 match 1 stars 4.10 score 25 scripts

pneuvial

adjclust:Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix

Implements a constrained version of hierarchical agglomerative clustering, in which each observation is associated to a position, and only adjacent clusters can be merged. Typical application fields in bioinformatics include Genome-Wide Association Studies or Hi-C data analysis, where the similarity between items is a decreasing function of their genomic distance. Taking advantage of this feature, the implemented algorithm is time and memory efficient. This algorithm is described in Ambroise et al (2019) <doi:10.1186/s13015-019-0157-4>.

Maintained by Pierre Neuvial. Last updated 5 months ago.

clustering featureextraction gwas hi-c hierarchical-clustering linkage-disequilibrium cpp openmp

2.5 match 16 stars 7.35 score 13 scripts 2 dependents

buttrey

treeClust:Cluster Distances Through Trees

Create a measure of inter-point dissimilarity useful for clustering mixed data, and, optionally, perform the clustering.

Maintained by Sam Buttrey. Last updated 7 years ago.

6.0 match 1 stars 3.06 score 77 scripts 5 dependents

marce10

warbleR:Streamline Bioacoustic Analysis

Functions aiming to facilitate the analysis of the structure of animal acoustic signals in 'R'. 'warbleR' makes use of the basic sound analysis tools from the packages 'tuneR' and 'seewave', and offers new tools for explore and quantify acoustic signal structure. The package allows to organize and manipulate multiple sound files, create spectrograms of complete recordings or individual signals in different formats, run several measures of acoustic structure, and characterize different structural levels in acoustic signals.

Maintained by Marcelo Araya-Salas. Last updated 2 months ago.

animal-acoustic-signals audio-processing bioacoustics spectrogram streamline-analysis cpp

1.7 match 54 stars 11.01 score 270 scripts 4 dependents

calvintchi

hierBipartite:Bipartite Graph-Based Hierarchical Clustering

Bipartite graph-based hierarchical clustering performs hierarchical clustering of groups of samples based on association patterns between two sets of variables. It is developed for pharmacogenomic datasets and datasets sharing the same data structure. In the context of pharmacogenomic datasets, the samples are cell lines, and the two sets of variables are typically expression levels and drug sensitivity values. For this method, sparse canonical correlation analysis from Lee, W., Lee, D., Lee, Y. and Pawitan, Y. (2011) <doi:10.2202/1544-6115.1638> is first applied to extract association patterns for each group of samples. Then, a nuclear norm-based dissimilarity measure is used to construct a dissimilarity matrix between groups based on the extracted associations. Finally, hierarchical clustering is applied.

Maintained by Calvin Chi. Last updated 4 years ago.

4.9 match 1 stars 3.70 score 4 scripts

cmmr

rbiom:Read/Write, Analyze, and Visualize 'BIOM' Data

A toolkit for working with Biological Observation Matrix ('BIOM') files. Read/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and beta diversity (including 'UniFrac'). Summarize counts by taxonomic level. Subset based on metadata. Generate visualizations and statistical analyses. CPU intensive operations are coded in C for speed.

Maintained by Daniel P. Smith. Last updated 6 days ago.

2.0 match 15 stars 9.02 score 117 scripts 6 dependents

tonigi

dtw:Dynamic Time Warping Algorithms

A comprehensive implementation of dynamic time warping (DTW) algorithms in R. DTW computes the optimal (least cumulative distance) alignment between points of two time series. Common DTW variants covered include local (slope) and global (window) constraints, subsequence matches, arbitrary distance definitions, normalizations, minimum variance matching, and so on. Provides cumulative distances, alignments, specialized plot styles, etc., as described in Giorgino (2009) <doi:10.18637/jss.v031.i07>.

Maintained by Toni Giorgino. Last updated 2 years ago.

2.0 match 5 stars 8.48 score 582 scripts 49 dependents

mikemeredith

wiqid:Quick and Dirty Estimates for Wildlife Populations

Provides simple, fast functions for maximum likelihood and Bayesian estimates of wildlife population parameters, suitable for use with simulated data or bootstraps. Early versions were indeed quick and dirty, but optional error-checking routines and meaningful error messages have been added. Includes single and multi-season occupancy, closed capture population estimation, survival, species richness and distance measures.

Maintained by Ngumbang Juat. Last updated 2 years ago.

3.4 match 2 stars 4.84 score 115 scripts 1 dependents

dmuellner

fastcluster:Fast Hierarchical Clustering Routines for R and 'Python'

This is a two-in-one package which provides interfaces to both R and 'Python'. It implements fast hierarchical, agglomerative clustering routines. Part of the functionality is designed as drop-in replacement for existing routines: linkage() in the 'SciPy' package 'scipy.cluster.hierarchy', hclust() in R's 'stats' package, and the 'flashClust' package. It provides the same functionality with the benefit of a much faster implementation. Moreover, there are memory-saving routines for clustering of vector data, which go beyond what the existing packages provide. For information on how to install the 'Python' files, see the file INSTALL in the source distribution. Based on the present package, Christoph Dalitz also wrote a pure 'C++' interface to 'fastcluster': <https://lionel.kr.hs-niederrhein.de/~dalitz/data/hclust/>.

Maintained by Daniel Müllner. Last updated 1 years ago.

cpp

1.8 match 10 stars 9.29 score 444 scripts 107 dependents

cran

OasisR:Outright Tool for the Analysis of Spatial Inequalities and Segregation

A comprehensive set of indexes and tests for social segregation analysis, as described in Tivadar (2019) - 'OasisR': An R Package to Bring Some Order to the World of Segregation Measurement <doi:10.18637/jss.v089.i07>. The package is the most complete existing tool and it clarifies many ambiguities and errors regarding the definition of segregation indices. Additionally, 'OasisR' introduces several resampling methods that enable testing their statistical significance (randomization tests, bootstrapping, and jackknife methods).

Maintained by Mihai Tivadar. Last updated 4 months ago.

8.8 match 2 stars 1.78 score 1 dependents

minatonakazawa

fmsb:Functions for Medical Statistics Book with some Demographic Data

Several utility functions for the book entitled "Practices of Medical and Health Data Analysis using R" (Pearson Education Japan, 2007) with Japanese demographic data and some demographic analysis related functions.

Maintained by Minato Nakazawa. Last updated 1 years ago.

2.0 match 3 stars 7.74 score 1.9k scripts 23 dependents

antoinelucas64

amap:Another Multidimensional Analysis Package

Tools for Clustering and Principal Component Analysis (With robust methods, and parallelized functions).

Maintained by Antoine Lucas. Last updated 5 months ago.

fortran cpp

2.0 match 7.66 score 460 scripts 26 dependents

zh2395

KMD:Kernel Measure of Multi-Sample Dissimilarity

Implementations of the kernel measure of multi-sample dissimilarity (KMD) between several samples using K-nearest neighbor graphs and minimum spanning trees. The KMD measures the dissimilarity between multiple samples, based on the observations from them. It converges to the population quantity (depending on the kernel) which is between 0 and 1. A small value indicates the multiple samples are from the same distribution, and a large value indicates the corresponding distributions are different. The population quantity is 0 if and only if all distributions are the same, and 1 if and only if all distributions are mutually singular. The package also implements the tests based on KMD for H0: the M distributions are equal against H1: not all the distributions are equal. Both permutation test and asymptotic test are available. These tests are consistent against all alternatives where at least two samples have different distributions. For more details on KMD and the associated tests, see Huang, Z. and B. Sen (2022) <arXiv:2210.00634>.

Maintained by Zhen Huang. Last updated 2 years ago.

5.6 match 1 stars 2.70 score 2 scripts

elaliberte

FD:Measuring Functional Diversity (FD) from Multiple Traits, and Other Tools for Functional Ecology

Computes different multidimensional FD indices. Implements a distance-based framework to measure FD that allows any number and type of functional traits, and can also consider species relative abundances. Also contains other useful tools for functional ecology.

Maintained by Etienne Laliberté. Last updated 1 years ago.

fortran

2.3 match 4 stars 6.54 score 586 scripts 15 dependents

ncss-tech

aqp:Algorithms for Quantitative Pedology

The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.

Maintained by Dylan Beaudette. Last updated 28 days ago.

digital-soil-mapping ncss-tech nrcs pedology pedometrics soil soil-survey usda

1.3 match 55 stars 11.77 score 1.2k scripts 2 dependents

daijiang

phyr:Model Based Phylogenetic Analysis

A collection of functions to do model-based phylogenetic analysis. It includes functions to calculate community phylogenetic diversity, to estimate correlations among functional traits while accounting for phylogenetic relationships, and to fit phylogenetic generalized linear mixed models. The Bayesian phylogenetic generalized linear mixed models are fitted with the 'INLA' package (<https://www.r-inla.org>).

Maintained by Daijiang Li. Last updated 1 years ago.

bayesian glmm inla phylogeny species-distribution-modeling openblas cpp

1.7 match 31 stars 8.67 score 107 scripts 2 dependents

cran

zetadiv:Functions to Compute Compositional Turnover Using Zeta Diversity

Functions to compute compositional turnover using zeta-diversity, the number of species shared by multiple assemblages. The package includes functions to compute zeta-diversity for a specific number of assemblages and to compute zeta-diversity for a range of numbers of assemblages. It also includes functions to explain how zeta-diversity varies with distance and with differences in environmental variables between assemblages, using generalised linear models, linear models with negative constraints, generalised additive models,shape constrained additive models, and I-splines.

Maintained by Guillaume Latombe. Last updated 3 years ago.

5.0 match 3 stars 2.89 score 64 scripts

cran

sets:Sets, Generalized Sets, Customizable Sets and Intervals

Data structures and basic operations for ordinary sets, generalizations such as fuzzy sets, multisets, and fuzzy multisets, customizable sets, and intervals.

Maintained by David Meyer. Last updated 1 years ago.

2.0 match 1 stars 7.20 score 592 scripts 109 dependents

lucymcgowan

pald:Partitioned Local Depth for Community Structure in Data

Implementation of the Partitioned Local Depth (PaLD) approach which provides a measure of local depth and the cohesion of a point to another which (together with a universal threshold for distinguishing strong and weak ties) may be used to reveal local and global structure in data, based on methods described in Berenhaut, Moore, and Melvin (2022) <doi:10.1073/pnas.2003634119>. No extraneous inputs, distributional assumptions, iterative procedures nor optimization criteria are employed. This package includes functions for computing local depths and cohesion as well as flexible functions for plotting community networks and displays of cohesion against distance.

Maintained by Lucy DAgostino McGowan. Last updated 11 months ago.

4.0 match 6 stars 3.56 score 12 scripts

laperez

Clustering:Techniques for Evaluating Clustering

The design of this package allows us to run different clustering packages and compare the results between them, to determine which algorithm behaves best from the data provided. See Martos, L.A.P., García-Vico, Á.M., González, P. et al.(2023) <doi:10.1007/s13748-022-00294-2> "Clustering: an R library to facilitate the analysis and comparison of cluster algorithms.", Martos, L.A.P., García-Vico, Á.M., González, P. et al. "A Multiclustering Evolutionary Hyperrectangle-Based Algorithm" <doi:10.1007/s44196-023-00341-3> and L.A.P., García-Vico, Á.M., González, P. et al. "An Evolutionary Fuzzy System for Multiclustering in Data Streaming" <doi:10.1016/j.procs.2023.12.058>.

Maintained by Luis Alfonso Perez Martos. Last updated 11 months ago.

3.5 match 5 stars 4.04 score 7 scripts

lvclark

polysat:Tools for Polyploid Microsatellite Analysis

A collection of tools to handle microsatellite data of any ploidy (and samples of mixed ploidy) where allele copy number is not known in partially heterozygous genotypes. It can import and export data in ABI 'GeneMapper', 'Structure', 'ATetra', 'Tetrasat'/'Tetra', 'GenoDive', 'SPAGeDi', 'POPDIST', 'STRand', and binary presence/absence formats. It can calculate pairwise distances between individuals using a stepwise mutation model or infinite alleles model, with or without taking ploidies and allele frequencies into account. These distances can be used for the calculation of clonal diversity statistics or used for further analysis in R. Allelic diversity statistics and Polymorphic Information Content are also available. polysat can assist the user in estimating the ploidy of samples, and it can estimate allele frequencies in populations, calculate pairwise or global differentiation statistics based on those frequencies, and export allele frequencies to 'SPAGeDi' and 'adegenet'. Functions are also included for assigning alleles to isoloci in cases where one pair of microsatellite primers amplifies alleles from two or more independently segregating isoloci. polysat is described by Clark and Jasieniuk (2011) <doi:10.1111/j.1755-0998.2011.02985.x> and Clark and Schreier (2017) <doi:10.1111/1755-0998.12639>.

Maintained by Lindsay V. Clark. Last updated 3 months ago.

cpp

1.8 match 11 stars 7.75 score 72 scripts 1 dependents

zdk123

pulsar:Parallel Utilities for Lambda Selection along a Regularization Path

Model selection for penalized graphical models using the Stability Approach to Regularization Selection ('StARS'), with options for speed-ups including Bounded StARS (B-StARS), batch computing, and other stability metrics (e.g., graphlet stability G-StARS). Christian L. Müller, Richard Bonneau, Zachary Kurtz (2016) <arXiv:1605.07072>.

Maintained by Zachary Kurtz. Last updated 1 years ago.

graphical-models

2.3 match 10 stars 6.16 score 65 scripts

gesistsa

webtrackR:Preprocessing and Analyzing Web Tracking Data

Data structures and methods to work with web tracking data. The functions cover data preprocessing steps, enriching web tracking data with external information and methods for the analysis of digital behavior as used in several academic papers (e.g., Clemm von Hohenberg et al., 2023 <doi:10.17605/OSF.IO/M3U9P>; Stier et al., 2022 <doi:10.1017/S0003055421001222>).

Maintained by David Schoch. Last updated 3 months ago.

webtracking

2.3 match 9 stars 6.03 score 8 scripts

pzhaonet

rarestR:Rarefaction-Based Species Richness Estimator

Calculate rarefaction-based alpha- and beta-diversity. Offer parametric extrapolation to estimate the total expected species in a single community and the total expected shared species between two communities. Visualize the curve-fitting for these estimators.

Maintained by Peng Zhao. Last updated 4 months ago.

biodiversity ecology

2.7 match 2 stars 4.89 score 13 scripts

bioc

MantelCorr:Compute Mantel Cluster Correlations

Computes Mantel cluster correlations from a (p x n) numeric data matrix (e.g. microarray gene-expression data).

Maintained by Brian Steinmeyer. Last updated 5 months ago.

clustering

3.9 match 3.30 score 1 scripts

mspinillos

ecoregime:Analysis of Ecological Dynamic Regimes

A toolbox for implementing the Ecological Dynamic Regime framework (Sánchez-Pinillos et al., 2023 <doi:10.1002/ecm.1589>) to characterize and compare groups of ecological trajectories in multidimensional spaces defined by state variables. The package includes the RETRA-EDR algorithm to identify representative trajectories, functions to generate, summarize, and visualize representative trajectories, and several metrics to quantify the distribution and heterogeneity of trajectories in an ecological dynamic regime and quantify the dissimilarity between two or more ecological dynamic regimes. The package also includes a set of functions to assess ecological resilience based on ecological dynamic regimes (Sánchez-Pinillos et al., 2024 <doi:10.1016/j.biocon.2023.110409>).

Maintained by Martina Sánchez-Pinillos. Last updated 11 months ago.

2.4 match 7 stars 5.32 score 8 scripts

chavent

ClustOfVar:Clustering of Variables

Cluster analysis of a set of variables. Variables can be quantitative, qualitative or a mixture of both.

Maintained by Marie Chavent. Last updated 5 years ago.

1.9 match 7 stars 6.47 score 142 scripts 2 dependents

silvialiverani

PReMiuM:Dirichlet Process Bayesian Clustering, Profile Regression

Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection. The main reference for the package is Liverani, Hastie, Azizi, Papathomas and Richardson (2015) <doi:10.18637/jss.v064.i07>.

Maintained by Silvia Liverani. Last updated 1 years ago.

cpp

3.9 match 3.13 score 126 scripts

bioc

timeOmics:Time-Course Multi-Omics data integration

timeOmics is a generic data-driven framework to integrate multi-Omics longitudinal data measured on the same biological samples and select key temporal features with strong associations within the same sample group. The main steps of timeOmics are: 1. Plaform and time-specific normalization and filtering steps; 2. Modelling each biological into one time expression profile; 3. Clustering features with the same expression profile over time; 4. Post-hoc validation step.

Maintained by Antoine Bodein. Last updated 5 months ago.

clustering featureextraction timecourse dimensionreduction software sequencing microarray metabolomics metagenomics proteomics classification regression immunooncology geneprediction multiplecomparison cluster integration multi-omics time-series

2.0 match 24 stars 5.98 score 10 scripts

swampthingpaul

NADA2:Data Analysis for Censored Environmental Data

Contains methods described by Dennis Helsel in his book "Statistics for Censored Environmental Data using Minitab and R" (2011) and courses and videos at <https://practicalstats.com>. This package adds new functions to the `NADA` Package.

Maintained by Paul Julian. Last updated 6 months ago.

1.9 match 15 stars 6.16 score 16 scripts

kurthornik

relations:Data Structures and Algorithms for Relations

Data structures and algorithms for k-ary relations with arbitrary domains, featuring relational algebra, predicate functions, and fitters for consensus relations.

Maintained by Kurt Hornik. Last updated 25 days ago.

2.3 match 5.04 score 58 scripts 14 dependents

stefanomp

yaConsensus:Consensus Clustering of Omic Data

Procedures to perform consensus clustering starting from a dissimilarity matrix or a data matrix. It's allowed to select if the subsampling has to be by samples or features. In case of computational heavy load, the procedures can run in parallel.

Maintained by Stefano Maria Pagnotta. Last updated 4 years ago.

fortran

4.1 match 2.70 score

cbolen1

rdi:Repertoire Dissimilarity Index

Methods for calculation and visualization of the Repertoire Dissimilarity Index. Citation: Bolen and Rubelt, et al (2017) <doi:10.1186/s12859-017-1556-5>.

Maintained by Christopher Bolen. Last updated 6 years ago.

3.9 match 2.88 score 15 scripts

mtrupiano1

knnwtsim:K Nearest Neighbor Forecasting with a Tailored Similarity Metric

Functions to implement K Nearest Neighbor forecasting using a weighted similarity metric tailored to the problem of forecasting univariate time series where recent observations, seasonal patterns, and exogenous predictors are all relevant in predicting future observations of the series in question. For more information on the formulation of this similarity metric please see Trupiano (2021) <arXiv:2112.06266>.

Maintained by Matthew Trupiano. Last updated 3 years ago.

forecasting knn-regression machine-learning time-series

4.0 match 1 stars 2.70 score 2 scripts

cran

fossil:Palaeoecological and Palaeogeographical Analysis Tools

A set of analytical tools useful in analysing ecological and geographical data sets, both ancient and modern. The package includes functions for estimating species richness (Chao 1 and 2, ACE, ICE, Jacknife), shared species/beta diversity, species area curves and geographic distances and areas.

Maintained by Matthew J. Vavrek. Last updated 5 years ago.

2.0 match 1 stars 5.18 score 532 scripts 7 dependents

carlosp-carmona

TPD:Methods for Measuring Functional Diversity Based on Trait Probability Density

Tools to calculate trait probability density functions (TPD) at any scale (e.g. populations, species, communities). TPD functions are used to compute several indices of functional diversity, as well as its partition across scales. These indices constitute a unified framework that incorporates the underlying probabilistic nature of trait distributions into uni- or multidimensional functional trait-based studies. See Carmona et al. (2016) <doi:10.1016/j.tree.2016.02.003> for further information.

Maintained by Carlos P. Carmona. Last updated 6 years ago.

3.0 match 2 stars 3.42 score 33 scripts

chavent

ClustGeo:Hierarchical Clustering with Spatial Constraints

Implements a Ward-like hierarchical clustering algorithm including soft spatial/geographical constraints.

Maintained by Marie Chavent. Last updated 3 years ago.

1.7 match 7 stars 5.85 score 67 scripts 1 dependents

cran

NST:Normalized Stochasticity Ratio

To estimate ecological stochasticity in community assembly. Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. The new index, normalized stochasticity ratio (NST), is to estimate ecological stochasticity, i.e. relative importance of stochastic processes, in community assembly. With functions in this package, NST can be calculated based on different similarity metrics and/or different null model algorithms, as well as some previous indexes, e.g. previous Stochasticity Ratio (ST), Standard Effect Size (SES), modified Raup-Crick metrics (RC). Functions for permutational test and bootstrapping analysis are also included. Previous ST is published by Zhou et al (2014) <doi:10.1073/pnas.1324044111>. NST is modified from ST by considering two alternative situations and normalizing the index to range from 0 to 1 (Ning et al 2019) <doi:10.1073/pnas.1904623116>. A modified version, MST, is a special case of NST, used in some recent or upcoming publications, e.g. Liang et al (2020) <doi:10.1016/j.soilbio.2020.108023>. SES is calculated as described in Kraft et al (2011) <doi:10.1126/science.1208584>. RC is calculated as reported by Chase et al (2011) <doi:10.1890/ES10-00117.1> and Stegen et al (2013) <doi:10.1038/ismej.2013.93>. Version 3 added NST based on phylogenetic beta diversity, used by Ning et al (2020) <doi:10.1038/s41467-020-18560-z>.

Maintained by Daliang Ning. Last updated 3 years ago.

3.4 match 2 stars 2.85 score 35 scripts

cran

FreeSortR:Free Sorting Data Analysis

Provides tools for describing and analysing free sorting data. Main methods are computation of consensus partition and factorial analysis of the dissimilarity matrix between stimuli (using multidimensional scaling approach).

Maintained by Philippe Courcoux. Last updated 7 years ago.

6.8 match 1.38 score 24 scripts

ajwills72

catlearn:Formal Psychological Models of Categorization and Learning

Formal psychological models of categorization and learning, independently-replicated data sets against which to test them, and simulation archives.

Maintained by Andy Wills. Last updated 3 months ago.

categorization cognitive-science formal-models learning learning-theory open-models open-science psychology cpp

1.8 match 26 stars 5.25 score 46 scripts

matthias-studer

WeightedCluster:Clustering of Weighted Data

Clusters state sequences and weighted data. It provides an optimized weighted PAM algorithm as well as functions for aggregating replicated cases, computing cluster quality measures for a range of clustering solutions and plotting (fuzzy) clusters of state sequences. Parametric bootstraps methods to validate typology of sequences are also provided. Finally, it provides a fuzzy and crisp CLARA algorithm to cluster large database with sequence analysis.

Maintained by Matthias Studer. Last updated 3 months ago.

cpp

1.7 match 5.55 score 106 scripts 4 dependents

tkcaccia

MetChem:Chemical Structural Similarity Analysis

A new pipeline to explore chemical structural similarity across metabolite. It allows to classify metabolites in structurally-related modules and identify common shared functional groups. KODAMA algorithm is used to highlight structural similarity between metabolites. See Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA. (2017) Bioinformatics <doi:10.1093/bioinformatics/btw705>, Cacciatore S, Luchinat C, Tenori L. (2014) Proc Natl Acad Sci USA <doi:10.1073/pnas.1220873111>, and Abdel-Shafy EA, Melak T, MacIntyre DA, Zadra G, Zerbini LF, Piazza S, Cacciatore S. (2023) Bioinformatics Advances <doi:10.1093/bioadv/vbad053>.

Maintained by Stefano Cacciatore. Last updated 2 years ago.

openjdk

4.5 match 2.00 score

cran

qdm:Fitting a Quadrilateral Dissimilarity Model to Same-Different Judgments

This package provides different specifications of a Quadrilateral Dissimilarity Model which can be used to fit same-different judgments in order to get a predicted matrix that satisfies regular minimality [Colonius & Dzhafarov, 2006, Measurement and representations of sensations, Erlbaum]. From such a matrix, Fechnerian distances can be computed.

Maintained by Nora Umbach. Last updated 10 years ago.

8.9 match 1.00 score

waddella

RnavGraphImageData:Image Data Used in the Loon Package Demos

Image data used as examples in the loon R package.

Maintained by Adrian Waddell. Last updated 7 years ago.

6.9 match 1.28 score 19 scripts

cran

CUB:A Class of Mixture Models for Ordinal Data

For ordinal rating data, estimate and test models within the family of CUB models and their extensions (where CUB stands for Combination of a discrete Uniform and a shifted Binomial distributions); Simulation routines, plotting facilities and fitting measures are also provided.

Maintained by Rosaria Simone. Last updated 1 years ago.

2.0 match 4.37 score 79 scripts 1 dependents

nakarinp

longreadvqs:Viral Quasispecies Comparison from Long-Read Sequencing Data

Performs variety of viral quasispecies diversity analyses [see Pamornchainavakul et al. (2024) <doi:10.21203/rs.3.rs-4637890/v1>] based on long-read sequence alignment. Main functions include 1) sequencing error and other noise minimization and read sampling, 2) Single nucleotide variant (SNV) profiles comparison, and 3) viral quasispecies profiles comparison and visualization.

Maintained by Nakarin Pamornchainavakul. Last updated 7 months ago.

1.8 match 4.65 score 4 scripts

yoctozepto

RAFS:Robust Aggregative Feature Selection

A cross-validated minimal-optimal feature selection algorithm. It utilises popularity counting, hierarchical clustering with feature dissimilarity measures, and prefiltering with all-relevant feature selection method to obtain the minimal-optimal set of features.

Maintained by Radosław Piliszek. Last updated 2 months ago.

6.0 match 1.30 score

gagolews

genie:Fast, Robust, and Outlier Resistant Hierarchical Clustering

Includes the reference implementation of Genie - a hierarchical clustering algorithm that links two point groups in such a way that an inequity measure (namely, the Gini index) of the cluster sizes does not significantly increase above a given threshold. This method most often outperforms many other data segmentation approaches in terms of clustering quality as tested on a wide range of benchmark datasets. At the same time, Genie retains the high speed of the single linkage approach, therefore it is also suitable for analysing larger data sets. For more details see (Gagolewski et al. 2016 <DOI:10.1016/j.ins.2016.05.003>). For an even faster and more feature-rich implementation, including, amongst others, noise point detection, see the 'genieclust' package (Gagolewski, 2021 <DOI:10.1016/j.softx.2021.100722>).

Maintained by Marek Gagolewski. Last updated 3 years ago.

cluster cluster-analysis clustering data-analysis data-mining data-science datascience genie hierarchical-clustering-algorithm machine-learning machine-learning-algorithms outliers cpp openmp

1.7 match 22 stars 4.55 score 16 scripts

cran

bios2mds:From Biological Sequences to Multidimensional Scaling

Utilities dedicated to the analysis of biological sequences by metric MultiDimensional Scaling with projection of supplementary data. It contains functions for reading multiple sequence alignment files, calculating distance matrices, performing metric multidimensional scaling and visualizing results.

Maintained by Marie Chabbert. Last updated 5 years ago.

4.0 match 1 stars 1.90 score

rajarshi

fingerprint:Functions to Operate on Binary Fingerprint Data

Functions to manipulate binary fingerprints of arbitrary length. A fingerprint is represented by an object of S4 class 'fingerprint' which is internally represented a vector of integers, such that each element represents the position in the fingerprint that is set to 1. The bitwise logical functions in R are overridden so that they can be used directly with 'fingerprint' objects. A number of distance metrics are also available (many contributed by Michael Fadock). Fingerprints can be converted to Euclidean vectors (i.e., points on the unit hypersphere) and can also be folded using OR. Arbitrary fingerprint formats can be handled via line handlers. Currently handlers are provided for CDK, MOE and BCI fingerprint data.

Maintained by Rajarshi Guha. Last updated 7 years ago.

1.8 match 4.22 score 82 scripts 12 dependents

kylebittinger

abdiv:Alpha and Beta Diversity Measures

A collection of measures for measuring ecological diversity. Ecological diversity comes in two flavors: alpha diversity measures the diversity within a single site or sample, and beta diversity measures the diversity across two sites or samples. This package overlaps considerably with other R packages such as 'vegan', 'gUniFrac', 'betapart', and 'fossil'. We also include a wide range of functions that are implemented in software outside the R ecosystem, such as 'scipy', 'Mothur', and 'scikit-bio'. The implementations here are designed to be basic and clear to the reader.

Maintained by Kyle Bittinger. Last updated 1 years ago.

1.8 match 9 stars 4.14 score 31 scripts

arliph

SPARTAAS:Statistical Pattern Recognition and daTing using Archaeological Artefacts assemblageS

Statistical pattern recognition and dating using archaeological artefacts assemblages. Package of statistical tools for archaeology. hclustcompro(perioclust): Bellanger Lise, Coulon Arthur, Husi Philibrary(SPARTlippe (2021, ISBN:978-3-030-60103-4). mapclust: Bellanger Lise, Coulon Arthur, Husi Philippe (2021) <doi:10.1016/j.jas.2021.105431>. seriograph: Desachy Bruno (2004) <doi:10.3406/pica.2004.2396>. cerardat: Bellanger Lise, Husi Philippe (2012) <doi:10.1016/j.jas.2011.06.031>.

Maintained by Arthur Coulon. Last updated 10 months ago.

1.8 match 6 stars 4.14 score 46 scripts

andregustavom

mlquantify:Algorithms for Class Distribution Estimation

Quantification is a prominent machine learning task that has received an increasing amount of attention in the last years. The objective is to predict the class distribution of a data sample. This package is a collection of machine learning algorithms for class distribution estimation. This package include algorithms from different paradigms of quantification. These methods are described in the paper: A. Maletzke, W. Hassan, D. dos Reis, and G. Batista. The importance of the test set size in quantification assessment. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI20, pages 2640–2646, 2020. <doi:10.24963/ijcai.2020/366>.

Maintained by Andre Maletzke. Last updated 3 years ago.

2.0 match 7 stars 3.54 score 1 scripts

marcohlmann

metanetwork:Handling and Representing Trophic Networks in Space and Time

A toolbox to handle and represent trophic networks in space or time across aggregation levels. This package contains a layout algorithm specifically designed for trophic networks, using dimension reduction on a diffusion graph kernel and trophic levels. Importantly, this package provides a layout method applicable for large trophic networks. The package also implements network diversity indices at different aggregation levels and connectance computation.

Maintained by Marc Ohlmann. Last updated 2 years ago.

1.8 match 2 stars 3.89 score 77 scripts

syksy

hamlet:Hierarchical Optimal Matching and Machine Learning Toolbox

Various functions and algorithms are provided here for solving optimal matching tasks in the context of preclinical cancer studies. Further, various helper and plotting functions are provided for unsupervised and supervised machine learning as well as longitudinal mixed-effects modeling of tumor growth response patterns.

Maintained by Teemu Daniel Laajala. Last updated 2 years ago.

1.7 match 4.18 score 25 scripts 2 dependents

jdmde

scellpam:Applying Partitioning Around Medoids to Single Cell Data with High Number of Cells

PAM (Partitioning Around Medoids) algorithm application to samples of single cell sequencing techniques with a high number of cells (as many as the computer memory allows). The package uses a binary format to store matrices (either full, sparse or symmetric) in files written in the disk that can contain any data type (not just double) which allows its manipulation when memory is sufficient to load them as int or float, but not as double. The PAM implementation is done in parallel, using several/all the cores of the machine, if it has them. This package shares a great part of its code with packages 'jmatrix' and 'parallelpam' but their functionality is included here so there is no need to install them.

Maintained by Juan Domingo. Last updated 8 months ago.

cpp

2.5 match 2.78 score 9 scripts

xytangtang

ProcData:Process Data Analysis

Provides tools for exploratory process data analysis. Process data refers to the data describing participants' problem-solving processes in computer-based assessments. It is often recorded in computer log files. This package provides functions to read, process, and write process data. It also implements two feature extraction methods to compress the information stored in process data into standard numerical vectors. This package also provides recurrent neural network based models that relate response processes with other binary or scale variables of interest. The functions that involve training and evaluating neural networks are wrappers of functions in 'keras'.

Maintained by Xueying Tang. Last updated 4 years ago.

cpp

1.8 match 10 stars 3.70 score 2 scripts

piusdahinden

disprofas:Non-Parametric Dissolution Profile Analysis

Similarity of dissolution profiles is assessed using the similarity factor f2 according to the EMA guideline (European Medicines Agency 2010) "On the investigation of bioequivalence". Dissolution profiles are regarded as similar if the f2 value is between 50 and 100. For the applicability of the similarity factor f2, the variability between profiles needs to be within certain limits. Often, this constraint is violated. One possibility in this situation is to resample the measured profiles in order to obtain a bootstrap estimate of f2 (Shah et al. (1998) <doi:10.1023/A:1011976615750>). Other alternatives are the model-independent non-parametric multivariate confidence region (MCR) procedure (Tsong et al. (1996) <doi:10.1177/009286159603000427>) or the T2-test for equivalence procedure (Hoffelder (2016) <https://www.ecv.de/suse_item.php?suseId=Z|pi|8430>). Functions for estimation of f1, f2, bootstrap f2, MCR / T2-test for equivalence procedure are implemented.

Maintained by Pius Dahinden. Last updated 9 months ago.

1.8 match 3.70 score 2 scripts

frederic-santos

AnthropMMD:An R Package for the Mean Measure of Divergence (MMD)

Offers a graphical user interface for the calculation of the mean measure of divergence, with facilities for trait selection and graphical representations <doi:10.1002/ajpa.23336>.

Maintained by Frédéric Santos. Last updated 1 years ago.

1.7 match 3.90 score 16 scripts

barnhilldave

TML:Tropical Geometry Tools for Machine Learning

Suite of tropical geometric tools for use in machine learning applications. These methods may be summarized in the following references: Yoshida, et al. (2022) <arxiv:2209.15045>, Barnhill et al. (2023) <arxiv:2303.02539>, Barnhill and Yoshida (2023) <doi:10.3390/math11153433>, Aliatimis et al. (2023) <arXiv:2306.08796>, Yoshida et al. (2022) <arXiv:2206.04206>, and Yoshida et al. (2019) <doi:10.1007/s11538-018-0493-4>.

Maintained by David Barnhill. Last updated 8 months ago.

1.8 match 3 stars 3.65 score 1 scripts

cran

optiSel:Optimum Contribution Selection and Population Genetics

A framework for the optimization of breeding programs via optimum contribution selection and mate allocation. An easy to use set of function for computation of optimum contributions of selection candidates, and of the population genetic parameters to be optimized. These parameters can be estimated using pedigree or genotype information, and include kinships, kinships at native haplotype segments, and breed composition of crossbred individuals. They are suitable for managing genetic diversity, removing introgressed genetic material, and accelerating genetic gain. Additionally, functions are provided for computing genetic contributions from ancestors, inbreeding coefficients, the native effective size, the native genome equivalent, pedigree completeness, and for preparing and plotting pedigrees. The methods are described in:\n Wellmann, R., and Pfeiffer, I. (2009) <doi:10.1017/S0016672309000202>.\n Wellmann, R., and Bennewitz, J. (2011) <doi:10.2527/jas.2010-3709>.\n Wellmann, R., Hartwig, S., Bennewitz, J. (2012) <doi:10.1186/1297-9686-44-34>.\n de Cara, M. A. R., Villanueva, B., Toro, M. A., Fernandez, J. (2013) <doi:10.1111/mec.12560>.\n Wellmann, R., Bennewitz, J., Meuwissen, T.H.E. (2014) <doi:10.1017/S0016672314000196>.\n Wellmann, R. (2019) <doi:10.1186/s12859-018-2450-5>.

Maintained by Robin Wellmann. Last updated 8 months ago.

cpp

1.8 match 1 stars 3.62 score

cogdisreslab

PAVER:PAVER: Pathway Analysis Visualization with Embedding Representations

Summary visualization using embedding representations to reveal underlying themes within sets of pathway terms.

Maintained by William G Ryan V. Last updated 8 months ago.

1.9 match 3.48 score 6 scripts

berchuck

spCP:Spatially Varying Change Points

Implements a spatially varying change point model with unique intercepts, slopes, variance intercepts and slopes, and change points at each location. Inference is within the Bayesian setting using Markov chain Monte Carlo (MCMC). The response variable can be modeled as Gaussian (no nugget), probit or Tobit link and the five spatially varying parameter are modeled jointly using a multivariate conditional autoregressive (MCAR) prior. The MCAR is a unique process that allows for a dissimilarity metric to dictate the local spatial dependencies. Full details of the package can be found in the accompanying vignette. Furthermore, the details of the package can be found in the corresponding paper on arXiv by Berchuck et al (2018): "A spatially varying change points model for monitoring glaucoma progression using visual field data", <arXiv:1811.11038>.

Maintained by Samuel I. Berchuck. Last updated 3 years ago.

openblas cpp

1.8 match 3.70 score 4 scripts

cran

SOMbrero:SOM Bound to Realize Euclidean and Relational Outputs

The stochastic (also called on-line) version of the Self-Organising Map (SOM) algorithm is provided. Different versions of the algorithm are implemented, for numeric and relational data and for contingency tables as described, respectively, in Kohonen (2001) <isbn:3-540-67921-9>, Olteanu & Villa-Vialaneix (2005) <doi:10.1016/j.neucom.2013.11.047> and Cottrell et al (2004) <doi:10.1016/j.neunet.2004.07.010>. The package also contains many plotting features (to help the user interpret the results), can handle (and impute) missing values and is delivered with a graphical user interface based on 'shiny'.

Maintained by Nathalie Vialaneix. Last updated 1 years ago.

1.5 match 1 stars 4.32 score 115 scripts 1 dependents

rekyt

fddimensionality:Test Effect of Traits of FD-Environment Relationship

Companion code for paper XXX <doi:xxx> on FD-Environment relationship, which tests to what extent we can expect FD-Environment trait relationship in function of number of traits included and type of environmental filtering.

Maintained by Matthias Grenié. Last updated 2 years ago.

3.8 match 1.70 score

bioc

AWFisher:An R package for fast computing for adaptively weighted fisher's method

Implementation of the adaptively weighted fisher's method, including fast p-value computing, variability index, and meta-pattern.

Maintained by Zhiguang Huo. Last updated 5 months ago.

statisticalmethod software

1.3 match 5 stars 4.70 score 4 scripts

cran

PoiClaClu:Classification and Clustering of Sequencing Data Based on a Poisson Model

Implements the methods described in the paper, Witten (2011) Classification and Clustering of Sequencing Data using a Poisson Model, Annals of Applied Statistics 5(4) 2493-2518.

Maintained by Daniela Witten. Last updated 6 years ago.

1.6 match 3.81 score 107 scripts 2 dependents

cran

TestDimorph:Analysis of the Interpopulation Difference in Degree of Sexual Dimorphism Using Summary Statistics

Offers a solution for the unavailability of raw data in most anthropological studies by facilitating the calculations of several sexual dimorphism related analyses using the published summary statistics of metric data (mean, standard deviation and sex specific sample size) as illustrated by the works of Relethford, J. H., & Hodges, D. C. (1985) <doi:10.1002/ajpa.1330660105>, Greene, D. L. (1989) <doi:10.1002/ajpa.1330790113> and Konigsberg, L. W. (1991) <doi:10.1002/ajpa.1330840110>.

Maintained by Bassam A. Abulnoor. Last updated 1 years ago.

2.3 match 1 stars 2.70 score

matthewkling

colors3d:Generate 2D and 3D Color Palettes

Generate multivariate color palettes to represent two-dimensional or three-dimensional data in graphics (in contrast to standard color palettes that represent just one variable). You tell 'colors3d' how to map color space onto your data, and it gives you a color for each data point. You can then use these colors to make plots in base 'R', 'ggplot2', or other graphics frameworks.

Maintained by Matthew Kling. Last updated 1 years ago.

1.8 match 3 stars 3.18 score 2 scripts

christopherkenny

divseg:Calculate Diversity and Segregation Indices

Implements common measures of diversity and spatial segregation. This package has tools to compute the majority of measures are reviewed in Massey and Denton (1988) <doi:10.2307/2579183>. Multiple common measures of within-geography diversity are implemented as well. All functions operate on data frames with a 'tidyselect' based workflow.

Maintained by Christopher T. Kenny. Last updated 10 months ago.

2.0 match 1 stars 2.78 score 12 scripts

cran

DisimForMixed:Calculate Dissimilarity Matrix for Dataset with Mixed Attributes

Implement the methods proposed by Ahmad & Dey (2007) <doi:10.1016/j.datak.2007.03.016> in calculating the dissimilarity matrix at the presence of mixed attributes. This Package includes functions to discretize quantitative variables, calculate conditional probability for each pair of attribute values, distance between every pair of attribute values, significance of attributes, calculate dissimilarity between each pair of objects.

Maintained by Hasanthi A. Pathberiya. Last updated 9 years ago.

5.5 match 1.00 score

jdmde

parallelpam:Parallel Partitioning-Around-Medoids (PAM) for Big Sets of Data

Application of the Partitioning-Around-Medoids (PAM) clustering algorithm described in Schubert, E. and Rousseeuw, P.J.: "Fast and eager k-medoids clustering: O(k) runtime improvement of the PAM, CLARA, and CLARANS algorithms." Information Systems, vol. 101, p. 101804, (2021). <doi:10.1016/j.is.2021.101804>. It uses a binary format for storing and retrieval of matrices developed for the 'jmatrix' package but the functionality of 'jmatrix' is included here, so you do not need to install it. Also, it is used by package 'scellpam', so if you have installed it, you do not need to install this package. PAM can be applied to sets of data whose dissimilarity matrix can be very big. It has been tested with up to 100.000 points. It does this with the help of the code developed for other package, 'jmatrix', which allows the matrix not to be loaded in 'R' memory (which would force it to be of double type) but it gets from disk, which allows using float (or even smaller data types). Moreover, the dissimilarity matrix is calculated in parallel if the computer has several cores so it can open many threads. The initial part of the PAM algorithm can be done with the BUILD or LAB algorithms; the BUILD algorithm has been implemented in parallel. The optimization phase implements the FastPAM1 algorithm, also in parallel. Finally, calculation of silhouette is available and also implemented in parallel.

Maintained by Juan Domingo. Last updated 8 months ago.

cpp

2.0 match 2.60 score 6 scripts

cran

benthos:Marine Benthic Ecosystem Analysis

Preprocessing tools and biodiversity measures (species abundance, species richness, population heterogeneity and sensitivity) for analysing marine benthic data. See Van Loon et al. (2015) <doi:10.1016/j.seares.2015.05.002> for an application of these tools.

Maintained by Dennis Walvoort. Last updated 3 years ago.

2.0 match 2.53 score 34 scripts

anloor7

mlmts:Machine Learning Algorithms for Multivariate Time Series

An implementation of several machine learning algorithms for multivariate time series. The package includes functions allowing the execution of clustering, classification or outlier detection methods, among others. It also incorporates a collection of multivariate time series datasets which can be used to analyse the performance of new proposed algorithms. Some of these datasets are stored in GitHub data packages 'ueadata1' to 'ueadata8'. To access these data packages, run 'install.packages(c('ueadata1', 'ueadata2', 'ueadata3', 'ueadata4', 'ueadata5', 'ueadata6', 'ueadata7', 'ueadata8'), repos='<https://anloor7.github.io/drat/>')'. The installation takes a couple of minutes but we strongly encourage the users to do it if they want to have available all datasets of mlmts. Practitioners from a broad variety of fields could benefit from the general framework provided by 'mlmts'.

Maintained by Angel Lopez-Oriona. Last updated 7 months ago.

5.0 match 1.00 score 2 scripts

martinoandrea92

gmfd:Inference and Clustering of Functional Data

Some methods for the inference and clustering of univariate and multivariate functional data, using a generalization of Mahalanobis distance, along with some functions useful for the analysis of functional data. For further details, see Martino A., Ghiglietti, A., Ieva, F. and Paganoni A. M. (2017) <arXiv:1708.00386>.

Maintained by Andrea Martino. Last updated 7 years ago.

2.0 match 1 stars 2.48 score 30 scripts

cran

ClusteredMutations:Location and Visualization of Clustered Somatic Mutations

Identification and visualization of groups of closely spaced mutations in the DNA sequence of cancer genome. The extremely mutated zones are searched in the symmetric dissimilarity matrix using the anti-Robinson matrix properties. Different data sets are obtained to describe and plot the clustered mutations information.

Maintained by David Lora. Last updated 9 years ago.

2.4 match 2.00 score

cran

SFS:Similarity-First Search Seriation Algorithm

An implementation of the Similarity-First Search algorithm (SFS), a combinatorial algorithm which can be used to solve the seriation problem and to recognize some structured weighted graphs. The SFS algorithm represents a generalization to weighted graphs of the graph search algorithm Lexicographic Breadth-First Search (Lex-BFS), a variant of Breadth-First Search. The SFS algorithm reduces to Lex-BFS when applied to binary matrices (or, equivalently, unweighted graphs). Hence this library can be also considered for Lex-BFS applications such as recognition of graph classes like chordal or unit interval graphs. In fact, the SFS seriation algorithm implemented in this package is a multisweep algorithm, which consists in repeating a finite number of SFS iterations (at most n sweeps for a matrix of size n). If the data matrix has a Robinsonian structure, then the ranking returned by the multistep SFS algorithm is a Robinson ordering of the input matrix. Otherwise the algorithm can be used as a heuristic to return a ranking partially satisfying the Robinson property.

Maintained by Utz-Uwe Haus. Last updated 6 years ago.

cpp

1.8 match 2.60 score 6 scripts

r-forge

stops:Structure Optimized Proximity Scaling

Methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodness-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,<doi:10.1007/s11222-022-10197-w>). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different 1-way MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. These cover essentially the functionality of the package smacofx, including Torgerson (classical) scaling with power transformations of dissimilarities, SMACOF MDS with powers of dissimilarities, Sammon mapping with powers of dissimilarities, elastic scaling with powers of dissimilarities, spherical SMACOF with powers of dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress MDS, MDS with powers of dissimilarities and configuration distances, elastic scaling powers of dissimilarities and configuration distances, Sammon mapping powers of dissimilarities and configuration distances, power stress MDS (POST-MDS), approximate power stress, Box-Cox MDS, local MDS, Isomap, curvilinear component analysis (CLCA), curvilinear distance analysis (CLDA) and sparsified (power) multidimensional scaling and (power) multidimensional distance analysis (experimental models from smacofx influenced by CLCA). All of these models can also be fit by optimizing over hyperparameters based on goodness-of-fit fit only (i.e., no structure considerations). The package further contains functions for optimization, specifically the adaptive Luus-Jaakola algorithm and a wrapper for Bayesian optimization with treed Gaussian process with jumps to linear models, and functions for various c-structuredness indices.

Maintained by Thomas Rusch. Last updated 2 months ago.

openjdk

1.0 match 1 stars 4.48 score 23 scripts

jcaledo

EnvNJ:Whole Genome Phylogenies Using Sequence Environments

Contains utilities for the analysis of protein sequences in a phylogenetic context. Allows the generation of phylogenetic trees base on protein sequences in an alignment-independent way. Two different methods have been implemented. One approach is based on the frequency analysis of n-grams, previously described in Stuart et al. (2002) <doi:10.1093/bioinformatics/18.1.100>. The other approach is based on the species-specific neighborhood preference around amino acids. Features include the conversion of a protein set into a vector reflecting these neighborhood preferences, pairwise distances (dissimilarity) between these vectors, and the generation of trees based on these distance matrices.

Maintained by Juan Carlos Aledo. Last updated 3 years ago.

4.3 match 1.04 score 11 scripts

cran

evclust:Evidential Clustering

Various clustering algorithms that produce a credal partition, i.e., a set of Dempster-Shafer mass functions representing the membership of objects to clusters. The mass functions quantify the cluster-membership uncertainty of the objects. The algorithms are: Evidential c-Means, Relational Evidential c-Means, Constrained Evidential c-Means, Evidential Clustering, Constrained Evidential Clustering, Evidential K-nearest-neighbor-based Clustering, Bootstrap Model-Based Evidential Clustering, Belief Peak Evidential Clustering, Neural-Network-based Evidential Clustering.

Maintained by Thierry Denoeux. Last updated 1 years ago.

1.8 match 2.48 score 1 dependents

ms609

Quartet:Comparison of Phylogenetic Trees Using Quartet and Split Measures

Calculates the number of four-taxon subtrees consistent with a pair of cladograms, calculating the symmetric quartet distance of Bandelt & Dress (1986), Reconstructing the shape of a tree from observed dissimilarity data, Advances in Applied Mathematics, 7, 309-343 <doi:10.1016/0196-8858(86)90038-2>, and using the tqDist algorithm of Sand et al. (2014), tqDist: a library for computing the quartet and triplet distances between binary or general trees, Bioinformatics, 30, 2079–2080 <doi:10.1093/bioinformatics/btu157> for pairs of binary trees.

Maintained by Martin R. Smith. Last updated 2 months ago.

bioinformatics comparison phylogenetic-trees phylogenetics quartet quartet-distance research-tool tree cpp

0.5 match 14 stars 8.00 score 40 scripts

noreastermt

allelematch:Identifying Unique Multilocus Genotypes where Genotyping Error and Missing Data may be Present

Tools for the identification of unique of multilocus genotypes when both genotyping error and missing data may be present; targeted for use with large datasets and databases containing multiple samples of each individual (a common situation in conservation genetics, particularly in non-invasive wildlife sampling applications). Functions explicitly incorporate missing data and can tolerate allele mismatches created by genotyping error. If you use this package, please cite the original publication in Molecular Ecology Resources (Galpern et al., 2012), the details for which can be generated using citation('allelematch'). For a complete vignette, please access via the Data S1 Supplementary documentation and tutorials (PDF) located at <doi:10.1111/j.1755-0998.2012.03137.x>.

Maintained by Todd Cross. Last updated 12 months ago.

1.8 match 2.26 score 8 scripts 1 dependents

nalimilan

RcmdrPlugin.temis:Graphical Integrated Text Mining Solution

An 'R Commander' plug-in providing an integrated solution to perform a series of text mining tasks such as importing and cleaning a corpus, and analyses like terms and documents counts, vocabulary tables, terms co-occurrences and documents similarity measures, time series analysis, correspondence analysis and hierarchical clustering. Corpora can be imported from spreadsheet-like files, directories of raw text files, 'Twitter' queries, as well as from 'Dow Jones Factiva', 'LexisNexis', 'Europresse' and 'Alceste' files.

Maintained by Milan Bouchet-Valat. Last updated 7 years ago.

3.9 match 1.00 score 7 scripts

cran

ddc:Distance Density Clustering Algorithm

A distance density clustering (DDC) algorithm in R. DDC uses dynamic time warping (DTW) to compute a similarity matrix, based on which cluster centers and cluster assignments are found. DDC inherits dynamic time warping (DTW) arguments and constraints. The cluster centers are centroid points that are calculated using the DTW Barycenter Averaging (DBA) algorithm. The clustering process is divisive. At each iteration, cluster centers are updated and data is reassigned to cluster centers. Early stopping is possible. The output includes cluster centers and clustering assignment, as described in the paper (Ma et al (2017) <doi:10.1109/ICDMW.2017.11>).

Maintained by Ruizhe Ma. Last updated 2 years ago.

1.9 match 2.00 score 9 scripts

green-striped-gecko

dartR.captive:Analysing 'SNP' Data to Support Captive Breeding

Functions are provided that facilitate the analysis of SNP (single nucleotide polymorphism) data to answer questions regarding captive breeding and relatedness between individuals. 'dartR.captive' is part of the 'dartRverse' suit of packages. Gruber et al. (2018) <doi:10.1111/1755-0998.12745>. Mijangos et al. (2022) <doi:10.1111/2041-210X.13918>.

Maintained by Bernd Gruber. Last updated 26 days ago.

1.8 match 1 stars 2.00 score 3 scripts

nowosad

supercells:Superpixels of Spatial Data

Creates superpixels based on input spatial data. This package works on spatial data with one variable (e.g., continuous raster), many variables (e.g., RGB rasters), and spatial patterns (e.g., areas in categorical rasters). It is based on the SLIC algorithm (Achanta et al. (2012) <doi:10.1109/TPAMI.2012.120>), and readapts it to work with arbitrary dissimilarity measures.

Maintained by Jakub Nowosad. Last updated 7 months ago.

rspatial spatial cpp

0.5 match 68 stars 6.50 score 52 scripts

biplab44

HDLSSkST:Distribution-Free Exact High Dimensional Low Sample Size k-Sample Tests

Testing homogeneity of k multivariate distributions is a classical and challenging problem in statistics, and this becomes even more challenging when the dimension of the data exceeds the sample size. We construct some tests for this purpose which are exact level (size) alpha tests based on clustering. These tests are easy to implement and distribution-free in finite sample situations. Under appropriate regularity conditions, these tests have the consistency property in HDLSS asymptotic regime, where the dimension of data grows to infinity while the sample size remains fixed. We also consider a multiscale approach, where the results for different number of partitions are aggregated judiciously. Details are in Biplab Paul, Shyamal K De and Anil K Ghosh (2021) <doi:10.1016/j.jmva.2021.104897>; Soham Sarkar and Anil K Ghosh (2019) <doi:10.1109/TPAMI.2019.2912599>; William M Rand (1971) <doi:10.1080/01621459.1971.10482356>; Cyrus R Mehta and Nitin R Patel (1983) <doi:10.2307/2288652>; Joseph C Dunn (1973) <doi:10.1080/01969727308546046>; Sture Holm (1979) <doi:10.2307/4615733>; Yoav Benjamini and Yosef Hochberg (1995) <doi: 10.2307/2346101>.

Maintained by Biplab Paul. Last updated 3 years ago.

cpp

3.3 match 1.00 score

shixiangwang

neopeptides:Calculate and Explore Property Indices of Neopeptides

Includes functions to calculate and explore several property indices for neopeptides, which are abnormal peptides generated from genome.

Maintained by Shixiang Wang. Last updated 3 years ago.

somaticmutation immunooncology alignment immunotherapy neoantigen peptides

1.8 match 1 stars 1.70 score 1 scripts

r-forge

smacofx:Flexible Multidimensional Scaling and 'smacof' Extensions

Flexible multidimensional scaling (MDS) methods and extensions to the package 'smacof'. This package contains various functions, wrappers, methods and classes for fitting, plotting and displaying a large number of different flexible MDS models. These are: Torgerson scaling (Torgerson, 1958, ISBN:978-0471879459) with powers, Sammon mapping (Sammon, 1969, <doi:10.1109/T-C.1969.222678>) with ratio and interval optimal scaling, Multiscale MDS (Ramsay, 1977, <doi:10.1007/BF02294052>) with ratio and interval optimal scaling, s-stress MDS (ALSCAL; Takane, Young & De Leeuw, 1977, <doi:10.1007/BF02293745>) with ratio and interval optimal scaling, elastic scaling (McGee, 1966, <doi:10.1111/j.2044-8317.1966.tb00367.x>) with ratio and interval optimal scaling, r-stress MDS (De Leeuw, Groenen & Mair, 2016, <https://rpubs.com/deleeuw/142619>) with ratio, interval, splines and nonmetric optimal scaling, power-stress MDS (POST-MDS; Buja & Swayne, 2002 <doi:10.1007/s00357-001-0031-0>) with ratio and interval optimal scaling, restricted power-stress (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>) with ratio and interval optimal scaling, approximate power-stress with ratio optimal scaling (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>), Box-Cox MDS (Chen & Buja, 2013, <https://jmlr.org/papers/v14/chen13a.html>), local MDS (Chen & Buja, 2009, <doi:10.1198/jasa.2009.0111>), curvilinear component analysis (Demartines & Herault, 1997, <doi:10.1109/72.554199>), curvilinear distance analysis (Lee, Lendasse & Verleysen, 2004, <doi:10.1016/j.neucom.2004.01.007>), nonlinear MDS with optimal dissimilarity powers functions (De Leeuw, 2024, <https://github.com/deleeuw/smacofManual/blob/main/smacofPO/smacofPO.pdf>), sparsified (power) MDS and sparsified multidimensional (power) distance analysis (Rusch, 2024, <doi:10.57938/355bf835-ddb7-42f4-8b85-129799fc240e>). Some functions are suitably flexible to allow any other sensible combination of explicit power transformations for weights, distances and input proximities with implicit ratio, interval, splines or nonmetric optimal scaling of the input proximities. Most functions use a Majorization-Minimization algorithm. Currently the methods are only available for one-mode data (symmetric dissimilarity matrices).

Maintained by Thomas Rusch. Last updated 2 months ago.

0.8 match 1 stars 3.89 score 2 dependents

brandmaier

pdc:Permutation Distribution Clustering

Permutation Distribution Clustering is a clustering method for time series. Dissimilarity of time series is formalized as the divergence between their permutation distributions. The permutation distribution was proposed as measure of the complexity of a time series.

Maintained by Andreas M. Brandmaier. Last updated 2 years ago.

0.5 match 6 stars 5.61 score 25 scripts 9 dependents

annechao

iNEXT.beta3D:Interpolation and Extrapolation with Beta Diversity for Three Dimensions of Biodiversity

As a sequel to 'iNEXT', the 'iNEXT.beta3D' package provides functions to compute standardized taxonomic, phylogenetic, and functional diversity (3D) estimates with a common sample size (for alpha and gamma diversity) or sample coverage (for alpha, beta, gamma diversity as well as dissimilarity or turnover indices). Hill numbers and their generalizations are used to quantify 3D and to make multiplicative decomposition (gamma = alpha x beta). The package also features size- and coverage-based rarefaction and extrapolation sampling curves to facilitate rigorous comparison of beta diversity across datasets. See Chao et al. (2023) <doi:10.1002/ecm.1588> for more details.

Maintained by Anne Chao. Last updated 4 months ago.

0.5 match 5.30 score 6 scripts

hms-dbmi

EHRtemporalVariability:Delineating Temporal Dataset Shifts in Electronic Health Records

Functions to delineate temporal dataset shifts in Electronic Health Records through the projection and visualization of dissimilarities among data temporal batches. This is done through the estimation of data statistical distributions over time and their projection in non-parametric statistical manifolds, uncovering the patterns of the data latent temporal variability. 'EHRtemporalVariability' is particularly suitable for multi-modal data and categorical variables with a high number of values, common features of biomedical data where traditional statistical process control or time-series methods may not be appropriate. 'EHRtemporalVariability' allows you to explore and identify dataset shifts through visual analytics formats such as Data Temporal heatmaps and Information Geometric Temporal (IGT) plots. An additional 'EHRtemporalVariability' Shiny app can be used to load and explore the package results and even to allow the use of these functions to those users non-experienced in R coding. (Sáez et al. 2020) <doi:10.1093/gigascience/giaa079>.

Maintained by Carlos Sáez. Last updated 11 months ago.

biomedical-data-science biomedical-informatics data-quality data-quality-monitoring dataset-shifts electronic-health-records time variability visualization

0.5 match 17 stars 5.27 score 22 scripts

marlonecobos

mop:Mobility Oriented-Parity Metric

A set of tools to perform multiple versions of the Mobility Oriented-Parity metric. This multivariate analysis helps to characterize levels of dissimilarity between a set of conditions of reference and another set of conditions of interest. If predictive models are transferred to conditions different from those over which models were calibrated (trained), this metric helps to identify transfer conditions that differ substantially from those of calibration. These tools are implemented following principles proposed in Owens et al. (2013) <doi:10.1016/j.ecolmodel.2013.04.011>, and expanded to obtain more detailed results that aid in interpretation.

Maintained by Marlon E. Cobos. Last updated 9 months ago.

cpp

0.5 match 7 stars 5.23 score 20 scripts 2 dependents

emf-creaf

ecotraj:Ecological Trajectory Analysis

Assists ecologists in the analysis of temporal changes of ecosystems, defined as trajectories on a chosen multivariate space, by providing a set of trajectory metrics and visual representations [De Caceres et al. (2019) <doi:10.1002/ecm.1350>; and Sturbois et al. (2021) <doi:10.1016/j.ecolmodel.2020.109400>]. Includes functions to estimate metrics for individual trajectories (length, directionality, angles, ...) as well as metrics to relate pairs of trajectories (dissimilarity and convergence). Functions are also provided to estimate the ecological quality of ecosystem with respect to reference conditions [Sturbois et al. (2023) <doi:10.1002/ecs2.4726>].

Maintained by Miquel De Cáceres. Last updated 18 days ago.

cpp

0.5 match 4 stars 5.21 score 21 scripts 1 dependents

plangfelder

moduleColor:Basic Module Functions

Methods for color labeling, calculation of eigengenes, merging of closely related modules.

Maintained by Peter Langfelder. Last updated 3 years ago.

1.9 match 1.28 score 19 scripts

bioc

BiRewire:High-performing routines for the randomization of a bipartite graph (or a binary event matrix), undirected and directed signed graph preserving degree distribution (or marginal totals)

Fast functions for bipartite network rewiring through N consecutive switching steps (See References) and for the computation of the minimal number of switching steps to be performed in order to maximise the dissimilarity with respect to the original network. Includes functions for the analysis of the introduced randomness across the switching steps and several other routines to analyse the resulting networks and their natural projections. Extension to undirected networks and directed signed networks is also provided. Starting from version 1.9.7 a more precise bound (especially for small network) has been implemented. Starting from version 2.2.0 the analysis routine is more complete and a visual montioring of the underlying Markov Chain has been implemented. Starting from 3.6.0 the library can handle also matrices with NA (not for the directed signed graphs). Since version 3.27.1 it is possible to add a constraint for dsg generation: usually positive and negative arc between two nodes could be not accepted.

Maintained by Andrea Gobbi. Last updated 5 months ago.

network

0.5 match 4.54 score 35 scripts

cran

spc4sts:Statistical Process Control for Stochastic Textured Surfaces

Provides statistical process control tools for stochastic textured surfaces. The current version supports the following tools: (1) generic modeling of stochastic textured surfaces. (2) local defect monitoring and diagnostics in stochastic textured surfaces, which was proposed by Bui and Apley (2018a) <doi:10.1080/00401706.2017.1302362>. (3) global change monitoring in the nature of stochastic textured surfaces, which was proposed by Bui and Apley (2018b) <doi:10.1080/00224065.2018.1507559>. (4) computation of dissimilarity matrix of stochastic textured surface images, which was proposed by Bui and Apley (2019b) <doi:10.1016/j.csda.2019.01.019>.

Maintained by Anh Tuan Bui. Last updated 3 years ago.

2.3 match 1.00 score

hvlieb

gromovlab:Gromov-Hausdorff Type Distances for Labeled Metric Spaces

Computes Gromov-Hausdorff type l^p distances for labeled metric spaces. These distances were introduced in V.Liebscher, Gromov meets Phylogenetics - new Animals for the Zoo of Metrics on Tree Space <arXiv:1504.05795> for phylogenetic trees, but may apply to a diversity of scenarios.

Maintained by Volkmar Liebscher. Last updated 4 years ago.

2.3 match 1 stars 1.00 score 1 scripts

gianluca-sottile

clustEff:Clusters of Effects Curves in Quantile Regression Models

Clustering method to cluster both effects curves, through quantile regression coefficient modeling, and curves in functional data analysis. Sottile G. and Adelfio G. (2019) <doi:10.1007/s00180-018-0817-8>.

Maintained by Gianluca Sottile. Last updated 1 years ago.

2.3 match 1.00 score 7 scripts

cran

mvcor:Correlation Coefficients for Multivariate Data

Correlation coefficients for multivariate data, namely the squared correlation coefficient and the RV coefficient (multivariate generalization of the squared Pearson correlation coefficient). References include Mardia K.V., Kent J.T. and Bibby J.M. (1979). "Multivariate Analysis". ISBN: 978-0124712522. London: Academic Press.

Maintained by Michail Tsagris. Last updated 2 months ago.

1.7 match 1.30 score

bioc

OMICsPCA:An R package for quantitative integration and analysis of multiple omics assays from heterogeneous samples

OMICsPCA is an analysis pipeline designed to integrate multi OMICs experiments done on various subjects (e.g. Cell lines, individuals), treatments (e.g. disease/control) or time points and to analyse such integrated data from various various angles and perspectives. In it's core OMICsPCA uses Principal Component Analysis (PCA) to integrate multiomics experiments from various sources and thus has ability to over data insufficiency issues by using the ingegrated data as representatives. OMICsPCA can be used in various application including analysis of overall distribution of OMICs assays across various samples /individuals /time points; grouping assays by user-defined conditions; identification of source of variation, similarity/dissimilarity between assays, variables or individuals.

Maintained by Subhadeep Das. Last updated 5 months ago.

immunooncology multiplecomparison principalcomponent datarepresentation workflow visualization dimensionreduction clustering biologicalquestion epigeneticsworkflow transcription geneticvariability gui biomedicalinformatics epigenetics functionalgenomics singlecell

0.5 match 4.00 score 1 scripts

mansukoh

bayMDS:Bayesian Multidimensional Scaling and Choice of Dimension

Bayesian approach to multidimensional scaling. The package consists of implementations of the methods of Oh and Raftery (2001) <doi:10.1198/016214501753208690>.

Maintained by Man-Suk Oh. Last updated 2 years ago.

openblas cpp

2.0 match 1.00 score 1 scripts

cran

FastCUB:Fast Estimation of CUB Models via Louis' Identity

For ordinal rating data, consider the accelerated EM algorithm to estimate and test models within the family of CUB models (where CUB stands for Combination of a discrete Uniform and a shifted Binomial distributions). The procedure is built upon Louis' identity for the observed information matrix. Best-subset variable selection is then implemented since it becomes more feasible from the computational point of view.

Maintained by Rosaria Simone. Last updated 1 years ago.

2.0 match 1 stars 1.00 score

manueleleonelli

bnmonitor:An Implementation of Sensitivity Analysis in Bayesian Networks

An implementation of sensitivity and robustness methods in Bayesian networks in R. It includes methods to perform parameter variations via a variety of co-variation schemes, to compute sensitivity functions and to quantify the dissimilarity of two Bayesian networks via distances and divergences. It further includes diagnostic methods to assess the goodness of fit of a Bayesian networks to data, including global, node and parent-child monitors. Reference: M. Leonelli, R. Ramanathan, R.L. Wilkerson (2022) <doi:10.1016/j.knosys.2023.110882>.

Maintained by Manuele Leonelli. Last updated 6 months ago.

0.5 match 3 stars 3.92 score 14 scripts

jlp2duke

EnsCat:Clustering of categorical data

This package implements the clustering methods of categorical data discussed in Amiri, S., Clarke, B. and Clarke J. (2015). Clustering categorical data via ensembling dissimilarity matrices. arXiv:1506.07930.

Maintained by Saeid Amiri. Last updated 8 years ago.

0.5 match 5 stars 3.74 score 22 scripts

aurora-torrente

briKmeans:Package for Brik, Fabrik and Fdebrik Algorithms to Initialise Kmeans

Implementation of the BRIk, FABRIk and FDEBRIk algorithms to initialise k-means. These methods are intended for the clustering of multivariate and functional data, respectively. They make use of the Modified Band Depth and bootstrap to identify appropriate initial seeds for k-means, which are proven to be better options than many techniques in the literature. Torrente and Romo (2021) <doi:10.1007/s00357-020-09372-3> It makes use of the functions kma and kma.similarity, from the archived package fdakma, by Alice Parodi et al.

Maintained by Aurora Torrente. Last updated 3 years ago.

1.8 match 1.00 score

cran

SegEnvIneq:Environmental Inequality Indices Based on Segregation Measures

A set of segregation-based indices and randomization methods to make robust environmental inequality assessments, as described in Schaeffer and Tivadar (2019) "Measuring Environmental Inequalities: Insights from the Residential Segregation Literature" <doi:10.1016/j.ecolecon.2019.05.009>.

Maintained by Mihai Tivadar. Last updated 4 months ago.

1.8 match 1.00 score

chiliubio

mecoturn:Decipher Microbial Turnover along a Gradient

Two pipelines are provided to study microbial turnover along a gradient, including the beta diversity and microbial abundance change. The 'betaturn' class consists of the steps of community dissimilarity matrix generation, matrix conversion, differential test and visualization. The workflow of 'taxaturn' class includes the taxonomic abundance calculation, abundance transformation, abundance change summary, statistical analysis and visualization. Multiple statistical approaches can contribute to the analysis of microbial turnover.

Maintained by Chi Liu. Last updated 6 months ago.

0.5 match 3 stars 3.48 score 6 scripts

vmielecnrs

econetwork:Analyzing Ecological Networks

A collection of advanced tools, methods and models specifically designed for analyzing different types of ecological networks - especially antagonistic (food webs, host-parasite), mutualistic (plant-pollinator, plant-fungus, etc) and competitive networks, as well as their variability in time and space. Statistical models are developed to describe and understand the mechanisms that determine species interactions, and to decipher the organization of these ecological networks (Ohlmann et al. (2019) <doi:10.1111/ele.13221>, Gonzalez et al. (2020) <doi:10.1101/2020.04.02.021691>, Miele et al. (2021) <doi:10.48550/arXiv.2103.10433>, Botella et al (2021) <doi:10.1111/2041-210X.13738>).

Maintained by Vincent Miele. Last updated 2 years ago.

gsl cpp openmp

1.7 match 1.04 score 11 scripts

cran

MultivariateAnalysis:Pacote Para Analise Multivariada

Package with multivariate analysis methodologies for experiment evaluation. The package estimates dissimilarity measures, builds dendrograms, obtains MANOVA, principal components, canonical variables, etc. (Pacote com metodologias de analise multivariada para avaliação de experimentos. O pacote estima medidas de dissimilaridade, construi de dendogramas, obtem a MANOVA, componentes principais, variaveis canonicas, etc.)

Maintained by Alcinei Mistico Azevedo. Last updated 11 months ago.

0.5 match 2.95 score

cran

bpcp:Beta Product Confidence Procedure for Right Censored Data

Calculates nonparametric pointwise confidence intervals for the survival distribution for right censored data, and for medians [Fay and Brittain <DOI:10.1002/sim.6905>]. Has two-sample tests for dissimilarity (e.g., difference, ratio or odds ratio) in survival at a fixed time, and differences in medians [Fay, Proschan, and Brittain <DOI:10.1111/biom.12231>]. Basically, the package gives exact inference methods for one- and two-sample exact inferences for Kaplan-Meier curves (e.g., generalizing Fisher's exact test to allow for right censoring), which are especially important for latter parts of the survival curve, small sample sizes or heavily censored data. Includes mid-p options.

Maintained by Michael P. Fay. Last updated 3 years ago.

0.5 match 2.97 score 3 dependents

cran

blockmodeling:Generalized and Classical Blockmodeling of Valued Networks

This is primarily meant as an implementation of generalized blockmodeling for valued networks. In addition, measures of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted: Žiberna (2007)<doi:10.1016/j.socnet.2006.04.002>, Žiberna (2008)<doi:10.1080/00222500701790207>, Žiberna (2014)<doi:10.1016/j.socnet.2014.04.002>.

Maintained by Aleš Žiberna. Last updated 2 years ago.

fortran

0.5 match 2.78 score 12 dependents

traminer

TraMineRextras:TraMineR Extension

Collection of ancillary functions and utilities to be used in conjunction with the 'TraMineR' package for sequence data exploration. Includes, among others, specific functions such as state survival plots, position-wise group-typical states, dynamic sequence indicators, and dissimilarities between event sequences. Also includes contributions by non-members of the TraMineR team such as methods for polyadic data and for the comparison of groups of sequences.

Maintained by Gilbert Ritschard. Last updated 7 months ago.

0.5 match 2.43 score 89 scripts 1 dependents

patnik

CIM:Compositional Impact of Migration

Produces statistical indicators of the impact of migration on the socio-demographic composition of an area. Three measures can be used: ratios, percentages and the Duncan index of dissimilarity. The input data files are assumed to be in an origin-destination matrix format, with each cell representing a flow count between an origin and a destination area. Columns are expected to represent origins, and rows are expected to represent destinations. The first row and column are assumed to contain labels for each area. See Rodriguez-Vignoli and Rowe (2018) <doi:10.1080/00324728.2017.1416155> for technical details.

Maintained by Nikos Patias. Last updated 6 years ago.

0.5 match 2.00 score 4 scripts

pmair78

semds:Structural Equation Multidimensional Scaling

Fits a structural equation multidimensional scaling (SEMDS) model for asymmetric and three-way input dissimilarities. It assumes that the dissimilarities are measured with errors. The latent dissimilarities are estimated as factor scores within an SEM framework while the objects are represented in a low-dimensional space as in MDS.

Maintained by Patrick Mair. Last updated 6 years ago.

1.0 match 1.00 score 7 scripts

hflavio12

cmahalanobis:Calculate Distance Measures for a Given List of Data Frames with Factors

It provides functions that calculate Mahalanobis distance, Euclidean distance, Manhattan distance, Chebyshev distance, Hamming distance, Canberra distance, Minkowski distance, Cosine distance, Bhattacharyya distance, Jaccard distance, Hellinger distance, Bray-Curtis distance, Sorensen-Dice distance between each pair of species in a list of data frames. These metrics are fundamental in various fields, such as cluster analysis, classification, and other applications of machine learning and data mining, where assessing similarity or dissimilarity between data is crucial. The package is designed to be flexible and easily integrated into data analysis workflows, providing reliable tools for evaluating distances in multidimensional contexts.

Maintained by Flavio Gioia. Last updated 2 months ago.

0.5 match 1.70 score

cran

FPDclustering:PD-Clustering and Related Methods

Probabilistic distance clustering (PD-clustering) is an iterative, distribution-free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership under the constraint that the product of the probability and the distance of each point to any cluster center is a constant. PD-clustering is a flexible method that can be used with elliptical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different sizes. GPDC and TPDC use a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high-dimensional data sets.

Maintained by Cristina Tortora. Last updated 10 days ago.

0.5 match 1.60 score

cran

fechner:Fechnerian Scaling of Discrete Object Sets

Functions and example datasets for Fechnerian scaling of discrete object sets. User can compute Fechnerian distances among objects representing subjective dissimilarities, and other related information. See package?fechner for an overview.

Maintained by Ali Uenlue. Last updated 9 years ago.

0.5 match 1.00 score 9 scripts

yushushi

aPCoA:Covariate Adjusted PCoA Plot

In fields such as ecology, microbiology, and genomics, non-Euclidean distances are widely applied to describe pairwise dissimilarity between samples. Given these pairwise distances, principal coordinates analysis (PCoA) is commonly used to construct a visualization of the data. However, confounding covariates can make patterns related to the scientific question of interest difficult to observe. We provide 'aPCoA' as an easy-to-use tool to improve data visualization in this context, enabling enhanced presentation of the effects of interest. Details are described in Yushu Shi, Liangliang Zhang, Kim-Anh Do, Christine Peterson and Robert Jenq (2020) Bioinformatics, Volume 36, Issue 13, 4099-4101.

Maintained by Yushu Shi. Last updated 3 years ago.

0.5 match 1.00 score 3 scripts

cran

pdcor:Fast and Light-Weight Partial Distance Correlation

Fast and memory-less computation of the partial distance correlation for vectors and matrices. Permutation-based and asymptotic hypothesis testing for zero partial distance correlation are also performed. References include: Szekely G. J. and Rizzo M. L. (2014). "Partial distance correlation with methods for dissimilarities". The Annals Statistics, 42(6): 2382--2412. <doi:10.1214/14-AOS1255>. Shen C., Panda S. and Vogelstein J. T. (2022). "The Chi-Square Test of Distance Correlation". Journal of Computational and Graphical Statistics, 31(1): 254--262. <doi:10.1080/10618600.2021.1938585>. Szekely G. J. and Rizzo M. L. (2023). "The Energy of Data and Distance Correlation". Chapman and Hall/CRC. <ISBN:9781482242744>.

Maintained by Michail Tsagris. Last updated 19 days ago.

0.5 match 1.00 score

whateverliu

GMKMcharlie:Unsupervised Gaussian Mixture and Minkowski and Spherical K-Means with Constraints

High performance trainers for parameterizing and clustering weighted data. The Gaussian mixture (GM) module includes the conventional EM (expectation maximization) trainer, the component-wise EM trainer, the minimum-message-length EM trainer by Figueiredo and Jain (2002) <doi:10.1109/34.990138>. These trainers accept additional constraints on mixture weights, covariance eigen ratios and on which mixture components are subject to update. The K-means (KM) module offers clustering with the options of (i) deterministic and stochastic K-means++ initializations, (ii) upper bounds on cluster weights (sizes), (iii) Minkowski distances, (iv) cosine dissimilarity, (v) dense and sparse representation of data input. The package improved the typical implementations of GM and KM algorithms in various aspects. It is carefully crafted in multithreaded C++ for modeling large data for industry use.

Maintained by Charlie Wusuo Liu. Last updated 4 years ago.

openblas cpp

0.5 match 1 stars 1.00 score

amarkos

manydist:Unbiased Distances for Mixed-Type Data

A comprehensive framework for calculating unbiased distances in datasets containing mixed-type variables (numerical and categorical). The package implements a general formulation that ensures multivariate additivity and commensurability, meaning that variables contribute equally to the overall distance regardless of their type, scale, or distribution. Supports multiple distance measures including Gower's distance, Euclidean distance, Manhattan distance, and various categorical variable distances such as simple matching, Eskin, occurrence frequency, and association-based distances. Provides tools for variable scaling (standard deviation, range, robust range, and principal component scaling), and handles both independent and association-based category dissimilarities. Implements methods to correct for biases that typically arise from different variable types, distributions, and number of categories. Particularly useful for cluster analysis, data visualization, and other distance-based methods when working with mixed data. Methods based on van de Velden et al. (2024) <doi:10.48550/arXiv.2411.00429> "Unbiased mixed variables distance".

Maintained by Angelos Markos. Last updated 1 months ago.

0.5 match 1.00 score