Showing 100 of total 100 results (show query)
easystats
correlation:Methods for Correlation Analysis
Lightweight package for computing different kinds of correlations, such as partial correlations, Bayesian correlations, multilevel correlations, polychoric correlations, biweight correlations, distance correlations and more. Part of the 'easystats' ecosystem. References: Makowski et al. (2020) <doi:10.21105/joss.02306>.
Maintained by Brenton M. Wiernik. Last updated 12 days ago.
bayesianbayesian-correlationsbiserialcorcorrelationcorrelation-analysiscorrelationseasystatsgammagaussian-graphical-modelshacktoberfestmatrixmultilevel-correlationsoutlierspartialpartial-correlationsregressionrobustspearman
11.0 match 439 stars 14.23 score 672 scripts 10 dependents
harrelfe
Hmisc:Harrell Miscellaneous
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.
Maintained by Frank E Harrell Jr. Last updated 2 days ago.
5.6 match 210 stars 17.61 score 17k scripts 750 dependents
mikejareds
hermiter:Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Nonparametric Correlation (Bivariate)
Facilitates estimation of full univariate and bivariate probability density functions and cumulative distribution functions along with full quantile functions (univariate) and nonparametric correlation (bivariate) using Hermite series based estimators. These estimators are particularly useful in the sequential setting (both stationary and non-stationary) and one-pass batch estimation setting for large data sets. Based on: Stephanou, Michael, Varughese, Melvin and Macdonald, Iain. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245>, Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z> and Stephanou, Michael and Varughese, Melvin. "Sequential estimation of Spearman rank correlation using Hermite series estimators." Journal of Multivariate Analysis (2021) <doi:10.1016/j.jmva.2021.104783>.
Maintained by Michael Stephanou. Last updated 7 months ago.
cumulative-distribution-functionkendall-correlation-coefficientonline-algorithmsprobability-density-functionquantilespearman-correlation-coefficientstatisticsstreaming-algorithmsstreaming-datacpp
16.1 match 15 stars 5.58 score 17 scripts
dgbonett
statpsych:Statistical Methods for Psychologists
Implements confidence interval and sample size methods that are especially useful in psychological research. The methods can be applied in 1-group, 2-group, paired-samples, and multiple-group designs and to a variety of parameters including means, medians, proportions, slopes, standardized mean differences, standardized linear contrasts of means, plus several measures of correlation and association. Confidence interval and sample size functions are given for single parameters as well as differences, ratios, and linear contrasts of parameters. The sample size functions can be used to approximate the sample size needed to estimate a parameter or function of parameters with desired confidence interval precision or to perform a variety of hypothesis tests (directional two-sided, equivalence, superiority, noninferiority) with desired power. For details see: Statistical Methods for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.
Maintained by Douglas G. Bonett. Last updated 3 months ago.
12.3 match 6 stars 4.83 score 15 scripts 1 dependents
astamm
roahd:Robust Analysis of High Dimensional Data
A collection of methods for the robust analysis of univariate and multivariate functional data, possibly in high-dimensional cases, and hence with attention to computational efficiency and simplicity of use. See the R Journal publication of Ieva et al. (2019) <doi:10.32614/RJ-2019-032> for an in-depth presentation of the 'roahd' package. See Aleman-Gomez et al. (2021) <arXiv:2103.08874> for details about the concept of depthgram.
Maintained by Aymeric Stamm. Last updated 3 years ago.
8.5 match 2 stars 6.29 score 164 scripts 2 dependents
psychmeta
psychmeta:Psychometric Meta-Analysis Toolkit
Tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more. Bugs can be reported to <https://github.com/psychmeta/psychmeta/issues> or <issues@psychmeta.com>.
Maintained by Jeffrey A. Dahlke. Last updated 9 months ago.
hacktoberfestmeta-analysispsychologypsychometricpsychometrics
6.3 match 57 stars 8.25 score 151 scripts
cmollica
MSmix:Finite Mixtures of Mallows Models with Spearman Distance for Full and Partial Rankings
Fit and analysis of finite Mixtures of Mallows models with Spearman Distance for full and partial rankings with arbitrary missing positions. Inference is conducted within the maximum likelihood framework via Expectation-Maximization algorithms. Estimation uncertainty is tackled via diverse versions of bootstrapping as well as via Hessian-based standard errors calculations. The most relevant reference of the methods is Crispino, Mollica, Astuti and Tardella (2023) <doi:10.1007/s11222-023-10266-8>.
Maintained by Cristina Mollica. Last updated 9 months ago.
31.8 match 1.48 score
maximeherve
RVAideMemoire:Testing and Plotting Procedures for Biostatistics
Contains miscellaneous functions useful in biostatistics, mostly univariate and multivariate testing procedures with a special emphasis on permutation tests. Many functions intend to simplify user's life by shortening existing procedures or by implementing plotting functions that can be used with as many methods from different packages as possible.
Maintained by Maxime HERVE. Last updated 1 years ago.
7.8 match 8 stars 5.31 score 632 scripts
patakamuri
modifiedmk:Modified Versions of Mann Kendall and Spearman's Rho Trend Tests
Power of non-parametric Mann-Kendall test and Spearman’s Rho test is highly influenced by serially correlated data. To address this issue, trend tests may be applied on the modified versions of the time series data by Block Bootstrapping (BBS), Prewhitening (PW) , Trend Free Prewhitening (TFPW), Bias Corrected Prewhitening and Variance Correction Approach by calculating effective sample size. Mann, H. B. (1945).<doi:10.1017/CBO9781107415324.004>. Kendall, M. (1975). Multivariate analysis. Charles Griffin&Company Ltd,. sen, P. K. (1968).<doi:10.2307/2285891>. Önöz, B., & Bayazit, M. (2012) <doi:10.1002/hyp.8438>. Hamed, K. H. (2009).<doi:10.1016/j.jhydrol.2009.01.040>. Yue, S., & Wang, C. Y. (2002) <doi:10.1029/2001WR000861>. Yue, S., Pilon, P., Phinney, B., & Cavadias, G. (2002) <doi:10.1002/hyp.1095>. Hamed, K. H., & Ramachandra Rao, A. (1998) <doi:10.1016/S0022-1694(97)00125-X>. Yue, S., & Wang, C. Y. (2004) <doi:10.1023/B:WARM.0000043140.61082.60>.
Maintained by Sandeep Kumar Patakamuri. Last updated 4 years ago.
6.9 match 4 stars 5.36 score 38 scripts 1 dependents
svetlanaeden
survSpearman:Nonparametric Spearman's Correlation for Survival Data
Nonparametric estimation of Spearman's rank correlation with bivariate survival (right-censored) data as described in Eden, S.K., Li, C., Shepherd B.E. (2021), Nonparametric Estimation of Spearman's Rank Correlation with Bivariate Survival Data, Biometrics (under revision). The package also provides functions that visualize bivariate survival data and bivariate probability mass function.
Maintained by Svetlana Eden. Last updated 2 years ago.
9.8 match 3.70 score 4 scripts
cran
pspearman:Spearman's Rank Correlation Test
Spearman's rank correlation test with precomputed exact null distribution for n <= 22.
Maintained by Petr Savicky. Last updated 3 years ago.
9.5 match 1 stars 3.73 score 35 scripts 3 dependents
r-forge
copula:Multivariate Dependence with Copulas
Classes (S4) of commonly used elliptical, Archimedean, extreme-value and other copula families, as well as their rotations, mixtures and asymmetrizations. Nested Archimedean copulas, related tools and special functions. Methods for density, distribution, random number generation, bivariate dependence measures, Rosenblatt transform, Kendall distribution function, perspective and contour plots. Fitting of copula models with potentially partly fixed parameters, including standard errors. Serial independence tests, copula specification tests (independence, exchangeability, radial symmetry, extreme-value dependence, goodness-of-fit) and model selection based on cross-validation. Empirical copula, smoothed versions, and non-parametric estimators of the Pickands dependence function.
Maintained by Martin Maechler. Last updated 11 days ago.
3.0 match 11.83 score 1.2k scripts 86 dependents
mlr-org
mlr3:Machine Learning in R - Next Generation
Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Maintained by Marc Becker. Last updated 4 days ago.
classificationdata-sciencemachine-learningmlr3regression
2.3 match 972 stars 14.86 score 2.3k scripts 35 dependents
american-institutes-for-research
wCorr:Weighted Correlations
Calculates Pearson, Spearman, polychoric, and polyserial correlation coefficients, in weighted or unweighted form. The package implements tetrachoric correlation as a special case of the polychoric and biserial correlation as a specific case of the polyserial.
Maintained by Paul Bailey. Last updated 2 years ago.
5.1 match 6.54 score 118 scripts 8 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.
3.7 match 3 stars 7.74 score 1.9k scripts 23 dependentsdgbonett
vcmeta:Varying Coefficient Meta-Analysis
Implements functions for varying coefficient meta-analysis methods. These methods do not assume effect size homogeneity. Subgroup effect size comparisons, general linear effect size contrasts, and linear models of effect sizes based on varying coefficient methods can be used to describe effect size heterogeneity. Varying coefficient meta-analysis methods do not require the unrealistic assumptions of the traditional fixed-effect and random-effects meta-analysis methods. For details see: Statistical Methods for Psychologists, Volume 5, <https://dgbonett.sites.ucsc.edu/>.
Maintained by Douglas G. Bonett. Last updated 8 months ago.
8.8 match 1 stars 3.00 score 8 scripts
bioc
bioDist:Different distance measures
A collection of software tools for calculating distance measures.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
4.3 match 5.89 score 64 scripts 2 dependentsbioc
scran:Methods for Single-Cell RNA-Seq Data Analysis
Implements miscellaneous functions for interpretation of single-cell RNA-seq data. Methods are provided for assignment of cell cycle phase, detection of highly variable and significantly correlated genes, identification of marker genes, and other common tasks in routine single-cell analysis workflows.
Maintained by Aaron Lun. Last updated 5 months ago.
immunooncologynormalizationsequencingrnaseqsoftwaregeneexpressiontranscriptomicssinglecellclusteringbioconductor-packagehuman-cell-atlassingle-cell-rna-seqopenblascpp
1.9 match 41 stars 13.14 score 7.6k scripts 36 dependents
bpfaff
QRM:Provides R-Language Code to Examine Quantitative Risk Management Concepts
Provides functions/methods to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Ruediger Frey, and Paul Embrechts.
Maintained by Bernhard Pfaff. Last updated 5 years ago.
5.3 match 4.53 score 181 scripts 5 dependentsbioc
miRLAB:Dry lab for exploring miRNA-mRNA relationships
Provide tools exploring miRNA-mRNA relationships, including popular miRNA target prediction methods, ensemble methods that integrate individual methods, functions to get data from online resources, functions to validate the results, and functions to conduct enrichment analyses.
Maintained by Thuc Duy Le. Last updated 5 months ago.
mirnageneexpressionnetworkinferencenetwork
5.0 match 4.72 score 11 scriptsbioc
PROMISE:PRojection Onto the Most Interesting Statistical Evidence
A general tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables as described in Pounds et. al. (2009) Bioinformatics 25: 2013-2019
Maintained by Stan Pounds. Last updated 5 months ago.
microarrayonechannelmultiplecomparisongeneexpression
4.0 match 5.44 score 46 scripts 1 dependentsr-forge
TopKLists:Inference, Aggregation and Visualization for Top-K Ranked Lists
For multiple ranked input lists (full or partial) representing the same set of N objects, the package TopKLists offers (1) statistical inference on the lengths of informative top-k lists, (2) stochastic aggregation of full or partial lists, and (3) graphical tools for the statistical exploration of input lists, and for the visualization of aggregation results.
Maintained by Michael G. Schimek. Last updated 9 years ago.
5.2 match 4.05 score 37 scripts 1 dependents
hzambran
hydroGOF:Goodness-of-Fit Functions for Comparison of Simulated and Observed Hydrological Time Series
S3 functions implementing both statistical and graphical goodness-of-fit measures between observed and simulated values, mainly oriented to be used during the calibration, validation, and application of hydrological models. Missing values in observed and/or simulated values can be removed before computations. Comments / questions / collaboration of any kind are very welcomed.
Maintained by Mauricio Zambrano-Bigiarini. Last updated 10 months ago.
1.9 match 40 stars 10.29 score 796 scripts 8 dependentsbioc
HybridMTest:Hybrid Multiple Testing
Performs hybrid multiple testing that incorporates method selection and assumption evaluations into the analysis using empirical Bayes probability (EBP) estimates obtained by Grenander density estimation. For instance, for 3-group comparison analysis, Hybrid Multiple testing considers EBPs as weighted EBPs between F-test and H-test with EBPs from Shapiro Wilk test of normality as weigth. Instead of just using EBPs from F-test only or using H-test only, this methodology combines both types of EBPs through EBPs from Shapiro Wilk test of normality. This methodology uses then the law of total EBPs.
Maintained by Demba Fofana. Last updated 5 months ago.
geneexpressiongeneticsmicroarray
3.9 match 4.38 score 5 scripts 1 dependents
ocbe-uio
contingencytables:Statistical Analysis of Contingency Tables
Provides functions to perform statistical inference of data organized in contingency tables. This package is a companion to the "Statistical Analysis of Contingency Tables" book by Fagerland et al. <ISBN 9781466588172>.
Maintained by Waldir Leoncio. Last updated 7 months ago.
3.8 match 3 stars 4.13 score 8 scripts 1 dependents
fcampelo
CALANGO:Comparative Analysis with Annotation-Based Genomic Components
A first-principle, phylogeny-aware comparative genomics tool for investigating associations between terms used to annotate genomic components (e.g., Pfam IDs, Gene Ontology terms,) with quantitative or rank variables such as number of cell types, genome size, or density of specific genomic elements. See the project website for more information, documentation and examples, and <doi:10.1016/j.patter.2023.100728> for the full paper.
Maintained by Felipe Campelo. Last updated 6 months ago.
3.2 match 2 stars 4.60 score 4 scriptscran
SuppDists:Supplementary Distributions
Ten distributions supplementing those built into R. Inverse Gauss, Kruskal-Wallis, Kendall's Tau, Friedman's chi squared, Spearman's rho, maximum F ratio, the Pearson product moment correlation coefficient, Johnson distributions, normal scores and generalized hypergeometric distributions.
Maintained by Thorsten Pohlert. Last updated 6 months ago.
2.8 match 5.14 score 78 dependents
salvatoremangiafico
rcompanion:Functions to Support Extension Education Program Evaluation
Functions and datasets to support Summary and Analysis of Extension Program Evaluation in R, and An R Companion for the Handbook of Biological Statistics. Vignettes are available at <https://rcompanion.org>.
Maintained by Salvatore Mangiafico. Last updated 30 days ago.
1.8 match 4 stars 8.01 score 2.4k scripts 5 dependents
helixcn
spaa:SPecies Association Analysis
Miscellaneous functions for analysing species association and niche overlap.
Maintained by Jinlong Zhang. Last updated 4 years ago.
1.9 match 12 stars 7.40 score 155 scripts 1 dependents
shengxintu
rankCorr:Total, Between-, and Within-cluster Spearman's Rank Correlations for Clustered Data
Estimates the total, between-, and within-cluster Spearman's rank correlations between two variables with clustered data.
Maintained by Shengxin Tu. Last updated 1 years ago.
5.0 match 2.70 scorecran
CTT:Classical Test Theory Functions
A collection of common test and item analyses from a classical test theory (CTT) framework. Analyses can be applied to both dichotomous and polytomous data. Functions provide reliability analyses (alpha), item statistics, disctractor analyses, disattenuated correlations, scoring routines, and empirical ICCs.
Maintained by John T. Willse. Last updated 7 years ago.
4.0 match 3.36 score 6 dependents
harrysouthworth
texmex:Statistical Modelling of Extreme Values
Statistical extreme value modelling of threshold excesses, maxima and multivariate extremes. Univariate models for threshold excesses and maxima are the Generalised Pareto, and Generalised Extreme Value model respectively. These models may be fitted by using maximum (optionally penalised-)likelihood, or Bayesian estimation, and both classes of models may be fitted with covariates in any/all model parameters. Model diagnostics support the fitting process. Graphical output for visualising fitted models and return level estimates is provided. For serially dependent sequences, the intervals declustering algorithm of Ferro and Segers (2003) <doi:10.1111/1467-9868.00401> is provided, with diagnostic support to aid selection of threshold and declustering horizon. Multivariate modelling is performed via the conditional approach of Heffernan and Tawn (2004) <doi:10.1111/j.1467-9868.2004.02050.x>, with graphical tools for threshold selection and to diagnose estimation convergence.
Maintained by Harry Southworth. Last updated 1 years ago.
1.9 match 7 stars 6.92 score 66 scripts 1 dependents
spiritspeak
rapidsplithalf:A Fast Permutation-Based Split-Half Reliability Algorithm
Accurately estimates the reliability of cognitive tasks using a fast and flexible permutation-based split-half reliability algorithm that supports stratified splitting while maintaining equal split sizes. See Kahveci, Bathke, and Blechert (2022) <doi:10.31234/osf.io/ta59r> for details.
Maintained by Sercan Kahveci. Last updated 11 days ago.
2.7 match 4.78 score 5 scriptsbioc
genefu:Computation of Gene Expression-Based Signatures in Breast Cancer
This package contains functions implementing various tasks usually required by gene expression analysis, especially in breast cancer studies: gene mapping between different microarray platforms, identification of molecular subtypes, implementation of published gene signatures, gene selection, and survival analysis.
Maintained by Benjamin Haibe-Kains. Last updated 4 months ago.
differentialexpressiongeneexpressionvisualizationclusteringclassification
1.7 match 7.42 score 193 scripts 3 dependents
kaigu1990
mcradds:Processing and Analyzing of Diagnostics Trials
Provides methods and functions to analyze the quantitative or qualitative performance for diagnostic assays, and outliers detection, reader precision and reference range are discussed. Most of the methods and algorithms refer to CLSI (Clinical & Laboratory Standards Institute) recommendations and NMPA (National Medical Products Administration) guidelines. In additional, relevant plots are constructed by 'ggplot2'.
Maintained by Kai Gu. Last updated 6 months ago.
3.1 match 1 stars 4.00 score 7 scripts
john-d-fox
RcmdrMisc:R Commander Miscellaneous Functions
Various statistical, graphics, and data-management functions used by the Rcmdr package in the R Commander GUI for R.
Maintained by John Fox. Last updated 1 years ago.
1.8 match 1 stars 7.00 score 432 scripts 42 dependentsbioc
compcodeR:RNAseq data simulation, differential expression analysis and performance comparison of differential expression methods
This package provides extensive functionality for comparing results obtained by different methods for differential expression analysis of RNAseq data. It also contains functions for simulating count data. Finally, it provides convenient interfaces to several packages for performing the differential expression analysis. These can also be used as templates for setting up and running a user-defined differential analysis workflow within the framework of the package.
Maintained by Charlotte Soneson. Last updated 3 months ago.
immunooncologyrnaseqdifferentialexpression
1.5 match 11 stars 8.06 score 26 scripts
numbats
cassowaryr:Compute Scagnostics on Pairs of Numeric Variables in a Data Set
Computes a range of scatterplot diagnostics (scagnostics) on pairs of numerical variables in a data set. A range of scagnostics, including graph and association-based scagnostics described by Leland Wilkinson and Graham Wills (2008) <doi:10.1198/106186008X320465> and association-based scagnostics described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be computed. Summary and plotting functions are provided.
Maintained by Harriet Mason. Last updated 11 days ago.
data-sciencedata-visualizationedahigh-dimensional-datamultivariate
2.0 match 3 stars 6.02 score 26 scripts 1 dependentscran
agricolae:Statistical Procedures for Agricultural Research
Original idea was presented in the thesis "A statistical analysis tool for agricultural research" to obtain the degree of Master on science, National Engineering University (UNI), Lima-Peru. Some experimental data for the examples come from the CIP and others research. Agricolae offers extensive functionality on experimental design especially for agricultural and plant breeding experiments, which can also be useful for other purposes. It supports planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, factorial, split and strip plot designs. There are also various analysis facilities for experimental data, e.g. treatment comparison procedures and several non-parametric tests comparison, biodiversity indexes and consensus cluster.
Maintained by Felipe de Mendiburu. Last updated 1 years ago.
1.7 match 7 stars 7.01 score 15 dependentsbioc
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.
clusteringfeatureextractiontimecoursedimensionreductionsoftwaresequencingmicroarraymetabolomicsmetagenomicsproteomicsclassificationregressionimmunooncologygenepredictionmultiplecomparisonclusterintegrationmulti-omicstime-series
2.0 match 24 stars 5.98 score 10 scripts
ecospat
ecospat:Spatial Ecology Miscellaneous Methods
Collection of R functions and data sets for the support of spatial ecology analyses with a focus on pre, core and post modelling analyses of species distribution, niche quantification and community assembly. Written by current and former members and collaborators of the ecospat group of Antoine Guisan, Department of Ecology and Evolution (DEE) and Institute of Earth Surface Dynamics (IDYST), University of Lausanne, Switzerland. Read Di Cola et al. (2016) <doi:10.1111/ecog.02671> for details.
Maintained by Olivier Broennimann. Last updated 1 months ago.
1.2 match 32 stars 9.35 score 418 scripts 1 dependentscran
gss:General Smoothing Splines
A comprehensive package for structural multivariate function estimation using smoothing splines.
Maintained by Chong Gu. Last updated 5 months ago.
1.7 match 3 stars 6.40 score 137 dependents
cbhurley
bullseye:Visualising Multiple Pairwise Variable Correlations and Other Scores
We provide a tidy data structure and visualisations for multiple or grouped variable correlations, general association measures scagnostics and other pairwise scores suitable for numerical, ordinal and nominal variables. Supported measures include distance correlation, maximal information, ace correlation, Kendall's tau, and polychoric correlation.
Maintained by Catherine Hurley. Last updated 9 days ago.
1.9 match 2 stars 5.58 score 14 scripts
scollinselliott
lakhesis:Consensus Seriation for Binary Data
Determining consensus seriations for binary incidence matrices, using a two-step process of Procrustes-fit correspondence analysis for heuristic selection of partial seriations and iterative regression to establish a single consensus. Contains the Lakhesis Calculator, a graphical platform for identifying seriated sequences. Collins-Elliott (2024) <https://volweb.utk.edu/~scolli46/sceLakhesis.pdf>.
Maintained by Stephen A. Collins-Elliott. Last updated 4 months ago.
archaeologybinary-datacorrespondence-analysisecologyseriation
2.0 match 4 stars 5.08 score 2 scriptsbioc
similaRpeak:Metrics to estimate a level of similarity between two ChIP-Seq profiles
This package calculates metrics which quantify the level of similarity between ChIP-Seq profiles. More specifically, the package implements six pseudometrics specialized in pattern similarity detection in ChIP-Seq profiles.
Maintained by Astrid Deschênes. Last updated 5 months ago.
biologicalquestionchipseqgeneticsmultiplecomparisondifferentialexpressionbioconductorbioconductor-packagechip-profileschip-seqmetrics
1.8 match 7 stars 5.62 score 7 scriptsbioc
knowYourCG:Functional analysis of DNA methylome datasets
KnowYourCG (KYCG) is a supervised learning framework designed for the functional analysis of DNA methylation data. Unlike existing tools that focus on genes or genomic intervals, KnowYourCG directly targets CpG dinucleotides, featuring automated supervised screenings of diverse biological and technical influences, including sequence motifs, transcription factor binding, histone modifications, replication timing, cell-type-specific methylation, and trait-epigenome associations. KnowYourCG addresses the challenges of data sparsity in various methylation datasets, including low-pass Nanopore sequencing, single-cell DNA methylomes, 5-hydroxymethylation profiles, spatial DNA methylation maps, and array-based datasets for epigenome-wide association studies and epigenetic clocks.
Maintained by Goldberg David. Last updated 2 months ago.
epigeneticsdnamethylationsequencingsinglecellspatialmethylationarrayzlib
1.7 match 2 stars 6.10 score 4 scripts
philipppro
measures:Performance Measures for Statistical Learning
Provides the biggest amount of statistical measures in the whole R world. Includes measures of regression, (multiclass) classification and multilabel classification. The measures come mainly from the 'mlr' package and were programed by several 'mlr' developers.
Maintained by Philipp Probst. Last updated 4 years ago.
2.3 match 1 stars 4.47 score 88 scripts 2 dependentsbioc
rcellminer:rcellminer: Molecular Profiles, Drug Response, and Chemical Structures for the NCI-60 Cell Lines
The NCI-60 cancer cell line panel has been used over the course of several decades as an anti-cancer drug screen. This panel was developed as part of the Developmental Therapeutics Program (DTP, http://dtp.nci.nih.gov/) of the U.S. National Cancer Institute (NCI). Thousands of compounds have been tested on the NCI-60, which have been extensively characterized by many platforms for gene and protein expression, copy number, mutation, and others (Reinhold, et al., 2012). The purpose of the CellMiner project (http://discover.nci.nih.gov/ cellminer) has been to integrate data from multiple platforms used to analyze the NCI-60 and to provide a powerful suite of tools for exploration of NCI-60 data.
Maintained by Augustin Luna. Last updated 5 months ago.
acghcellbasedassayscopynumbervariationgeneexpressionpharmacogenomicspharmacogeneticsmirnacheminformaticsvisualizationsoftwaresystemsbiology
1.8 match 5.71 score 113 scripts
doebler
mada:Meta-Analysis of Diagnostic Accuracy
Provides functions for diagnostic meta-analysis. Next to basic analysis and visualization the bivariate Model of Reitsma et al. (2005) that is equivalent to the HSROC of Rutter & Gatsonis (2001) can be fitted. A new approach based to diagnostic meta-analysis of Holling et al. (2012) is also available. Standard methods like summary, plot and so on are provided.
Maintained by Philipp Doebler. Last updated 3 years ago.
1.9 match 2 stars 5.09 score 58 scripts 3 dependents
mjafin
GeneCycle:Identification of Periodically Expressed Genes
The GeneCycle package implements the approaches of Wichert et al. (2004) <doi:10.1093/bioinformatics/btg364>, Ahdesmaki et al. (2005) <doi:10.1186/1471-2105-6-117> and Ahdesmaki et al. (2007) <DOI:10.1186/1471-2105-8-233> for detecting periodically expressed genes from gene expression time series data.
Maintained by Miika Ahdesmaki. Last updated 4 years ago.
3.3 match 1 stars 2.81 score 64 scripts
sigbertklinke
exams.forge:Support for Compiling Examination Tasks using the 'exams' Package
The main aim is to further facilitate the creation of exercises based on the package 'exams' by Grün, B., and Zeileis, A. (2009) <doi:10.18637/jss.v029.i10>. Creating effective student exercises involves challenges such as creating appropriate data sets and ensuring access to intermediate values for accurate explanation of solutions. The functionality includes the generation of univariate and bivariate data including simple time series, functions for theoretical distributions and their approximation, statistical and mathematical calculations for tasks in basic statistics courses as well as general tasks such as string manipulation, LaTeX/HTML formatting and the editing of XML task files for 'Moodle'.
Maintained by Sigbert Klinke. Last updated 8 months ago.
3.4 match 2.70 score 1 scripts
yijin-zeng
bosfr:Computes Exact Bounds of Spearman's Footrule with Missing Data
Computes exact bounds of Spearman's footrule in the presence of missing data, and performs independence test based on the bounds with controlled Type I error regardless of the values of missing data. Suitable only for distinct, univariate data where no ties is allowed.
Maintained by Yijin Zeng. Last updated 2 months ago.
5.1 match 1.70 score
gesistsa
sweater:Speedy Word Embedding Association Test and Extras Using R
Conduct various tests for evaluating implicit biases in word embeddings: Word Embedding Association Test (Caliskan et al., 2017), <doi:10.1126/science.aal4230>, Relative Norm Distance (Garg et al., 2018), <doi:10.1073/pnas.1720347115>, Mean Average Cosine Similarity (Mazini et al., 2019) <arXiv:1904.04047>, SemAxis (An et al., 2018) <arXiv:1806.05521>, Relative Negative Sentiment Bias (Sweeney & Najafian, 2019) <doi:10.18653/v1/P19-1162>, and Embedding Coherence Test (Dev & Phillips, 2019) <arXiv:1901.07656>.
Maintained by Chung-hong Chan. Last updated 1 months ago.
bias-detectiontextanalysiswordembeddingcpp
1.8 match 30 stars 4.80 score 14 scriptscran
ecotoxicology:Methods for Ecotoxicology
Implementation of the EPA's Ecological Exposure Research Division (EERD) tools (discontinued in 1999) for Probit and Trimmed Spearman-Karber Analysis. Probit and Spearman-Karber methods from Finney's book "Probit analysis a statistical treatment of the sigmoid response curve" with options for most accurate results or identical results to the book. Probit and all the tables from Finney's book (code-generated, not copied) with the generating functions included. Control correction: Abbott, Schneider-Orelli, Henderson-Tilton, Sun-Shepard. Toxicity scales: Horsfall-Barratt, Archer, Gauhl-Stover, Fullerton-Olsen, etc.
Maintained by Jose Gama. Last updated 9 years ago.
4.5 match 3 stars 1.89 score 26 scriptsbioc
csdR:Differential gene co-expression
This package contains functionality to run differential gene co-expression across two different conditions. The algorithm is inspired by Voigt et al. 2017 and finds Conserved, Specific and Differentiated genes (hence the name CSD). This package include efficient and variance calculation by bootstrapping and Welford's algorithm.
Maintained by Jakob Peder Pettersen. Last updated 4 months ago.
differentialexpressiongraphandnetworkgeneexpressionnetworkcppopenmp
1.8 match 7 stars 4.85 score 7 scripts
xluo11
xxIRT:Item Response Theory and Computer-Based Testing
A suite of psychometric analysis tools for research and operation, including: (1) computation of probability, information, and likelihood for the 3PL, GPCM, and GRM; (2) parameter estimation using joint or marginal likelihood estimation method; (3) simulation of computerized adaptive testing using built-in or customized algorithms; (4) assembly and simulation of multistage testing. The full documentation and tutorials are at <https://github.com/xluo11/xxIRT>.
Maintained by Xiao Luo. Last updated 6 years ago.
2.0 match 25 stars 4.10 score 10 scripts
tfletcher05
psychometric:Applied Psychometric Theory
Contains functions useful for correlation theory, meta-analysis (validity-generalization), reliability, item analysis, inter-rater reliability, and classical utility.
Maintained by Thomas D. Fletcher. Last updated 1 years ago.
1.9 match 4.24 score 181 scripts 1 dependents
bouchranasri
MixedIndTests:Tests of Randomness and Tests of Independence
Functions for testing randomness for a univariate time series with arbitrary distribution (discrete, continuous, mixture of both types) and for testing independence between random variables with arbitrary distributions. The test statistics are based on the multilinear empirical copula and multipliers are used to compute P-values. The test of independence between random variables appeared in Genest, Nešlehová, Rémillard & Murphy (2019) and the test of randomness appeared in Nasri (2022).
Maintained by Bouchra R. Nasri. Last updated 1 years ago.
5.1 match 1.48 score 6 scripts 1 dependents
peteryinr
YRmisc:Y&R Miscellaneous R Functions
Miscellaneous functions for data analysis, portfolio management, graphics, data manipulation, statistical investigation, including descriptive statistics, creating leading and lagging variables, portfolio return analysis, time series difference and percentage change calculation, stacking data for higher efficient analysis.
Maintained by Xuanhua (Peter) Yin. Last updated 5 years ago.
4.3 match 1.76 score 57 scripts
modal-inria
Rankcluster:Model-Based Clustering for Multivariate Partial Ranking Data
Implementation of a model-based clustering algorithm for ranking data (C. Biernacki, J. Jacques (2013) <doi:10.1016/j.csda.2012.08.008>). Multivariate rankings as well as partial rankings are taken into account. This algorithm is based on an extension of the Insertion Sorting Rank (ISR) model for ranking data, which is a meaningful and effective model parametrized by a position parameter (the modal ranking, quoted by mu) and a dispersion parameter (quoted by pi). The heterogeneity of the rank population is modelled by a mixture of ISR, whereas conditional independence assumption is considered for multivariate rankings.
Maintained by Quentin Grimonprez. Last updated 2 years ago.
clusteringhacktoberfestrankcpp
1.9 match 1 stars 3.74 score 37 scripts 1 dependentsbioc
abseqR:Reporting and data analysis functionalities for Rep-Seq datasets of antibody libraries
AbSeq is a comprehensive bioinformatic pipeline for the analysis of sequencing datasets generated from antibody libraries and abseqR is one of its packages. abseqR empowers the users of abseqPy (https://github.com/malhamdoosh/abseqPy) with plotting and reporting capabilities and allows them to generate interactive HTML reports for the convenience of viewing and sharing with other researchers. Additionally, abseqR extends abseqPy to compare multiple repertoire analyses and perform further downstream analysis on its output.
Maintained by JiaHong Fong. Last updated 5 months ago.
sequencingvisualizationreportwritingqualitycontrolmultiplecomparison
1.8 match 4.00 score 3 scripts
mthrun
DRquality:Quality Measurements for Dimensionality Reduction
Several quality measurements for investigating the performance of dimensionality reduction methods are provided here. In addition a new quality measurement called Gabriel classification error is made accessible.
Maintained by Michael Thrun. Last updated 2 years ago.
3.4 match 2.00 score
alexcannon
MBC:Multivariate Bias Correction of Climate Model Outputs
Calibrate and apply multivariate bias correction algorithms for climate model simulations of multiple climate variables. Three methods described by Cannon (2016) <doi:10.1175/JCLI-D-15-0679.1> and Cannon (2018) <doi:10.1007/s00382-017-3580-6> are implemented — (i) MBC Pearson correlation (MBCp), (ii) MBC rank correlation (MBCr), and (iii) MBC N-dimensional PDF transform (MBCn) — as is the Rank Resampling for Distributions and Dependences (R2D2) method.
Maintained by Alex J. Cannon. Last updated 4 months ago.
1.8 match 6 stars 3.76 score 16 scripts 1 dependents
drordas
D2MCS:Data Driving Multiple Classifier System
Provides a novel framework to able to automatically develop and deploy an accurate Multiple Classifier System based on the feature-clustering distribution achieved from an input dataset. 'D2MCS' was developed focused on four main aspects: (i) the ability to determine an effective method to evaluate the independence of features, (ii) the identification of the optimal number of feature clusters, (iii) the training and tuning of ML models and (iv) the execution of voting schemes to combine the outputs of each classifier comprising the Multiple Classifier System.
Maintained by Miguel Ferreiro-Díaz. Last updated 3 years ago.
1.8 match 3.70 score
yunyishen
robustcov:Collection of Robust Covariance and (Sparse) Precision Matrix Estimators
Collection of methods for robust covariance and (sparse) precision matrix estimation based on Loh and Tan (2018) <doi:10.1214/18-EJS1427>.
Maintained by Yunyi Shen. Last updated 4 years ago.
precision-matrixrobust-estimatesopenblascppopenmp
2.3 match 1 stars 2.70 score
cran
ufs:A Collection of Utilities
This is a new version of the 'userfriendlyscience' package, which has grown a bit unwieldy. Therefore, distinct functionalities are being 'consciously uncoupled' into different packages. This package contains the general-purpose tools and utilities (see the 'behaviorchange' package, the 'rosetta' package, and the soon-to-be-released 'scd' package for other functionality), and is the most direct 'successor' of the original 'userfriendlyscience' package. For example, this package contains a number of basic functions to create higher level plots, such as diamond plots, to easily plot sampling distributions, to generate confidence intervals, to plan study sample sizes for confidence intervals, and to do some basic operations such as (dis)attenuate effect size estimates.
Maintained by Gjalt-Jorn Peters. Last updated 1 years ago.
2.0 match 2.95 score 3 dependents
fbartos
IRR2FPR:Computing False Positive Rate from Inter-Rater Reliability
Implements a 'Shiny Item Analysis' module and functions for computing false positive rate and other binary classification metrics from inter-rater reliability based on Bartoš & Martinková (2022) <doi:10.48550/arXiv.2207.09101>.
Maintained by František Bartoš. Last updated 11 months ago.
1.8 match 1 stars 3.00 score 3 scripts
extremestats
spearmanCI:Jackknife Euclidean / Empirical Likelihood Inference for Spearman's Rho
Functions for conducting jackknife Euclidean / empirical likelihood inference for Spearman's rho (de Carvalho and Marques (2012) <doi:10.1080/10920277.2012.10597644>).
Maintained by Miguel de Carvalho. Last updated 10 months ago.
5.1 match 1.00 score 2 scriptsocbe-uio
BayesMallows:Bayesian Preference Learning with the Mallows Rank Model
An implementation of the Bayesian version of the Mallows rank model (Vitelli et al., Journal of Machine Learning Research, 2018 <https://jmlr.org/papers/v18/15-481.html>; Crispino et al., Annals of Applied Statistics, 2019 <doi:10.1214/18-AOAS1203>; Sorensen et al., R Journal, 2020 <doi:10.32614/RJ-2020-026>; Stein, PhD Thesis, 2023 <https://eprints.lancs.ac.uk/id/eprint/195759>). Both Metropolis-Hastings and sequential Monte Carlo algorithms for estimating the models are available. Cayley, footrule, Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the posterior distributions of parameters are provided. The package also provides functions for estimating the partition function (normalizing constant) of the Mallows rank model, both with the importance sampling algorithm of Vitelli et al. and asymptotic approximation with the IPFP algorithm (Mukherjee, Annals of Statistics, 2016 <doi:10.1214/15-AOS1389>).
Maintained by Oystein Sorensen. Last updated 1 months ago.
mallows-modelopenblascppopenmp
0.5 match 21 stars 7.91 score 36 scripts 1 dependents
eliebs
depcoeff:Dependency Coefficients
Functions to compute coefficients measuring the dependence of two or more than two variables. The functions can be deployed to gain information about functional dependencies of the variables with emphasis on monotone functions. The statistics describe how well one response variable can be approximated by a monotone function of other variables. In regression analysis the variable selection is an important issue. In this framework the functions could be useful tools in modeling the regression function. Detailed explanations on the subject can be found in papers Liebscher (2014) <doi:10.2478/demo-2014-0004>; Liebscher (2017) <doi:10.1515/demo-2017-0012>; Liebscher (2019, submitted).
Maintained by Eckhard Liebscher. Last updated 5 years ago.
3.8 match 1.00 scorebouchranasri
CopulaInference:Estimation and Goodness-of-Fit of Copula-Based Models with Arbitrary Distributions
Estimation and goodness-of-fit functions for copula-based models of bivariate data with arbitrary distributions (discrete, continuous, mixture of both types). The copula families considered here are the Gaussian, Student, Clayton, Frank, Gumbel, Joe, Plackett, BB1, BB6, BB7,BB8, together with the following non-central squared copula families in Nasri (2020) <doi:10.1016/j.spl.2020.108704>: ncs-gaussian, ncs-clayton, ncs-gumbel, ncs-frank, ncs-joe, and ncs-plackett. For theoretical details, see, e.g., Nasri and Remillard (2023) <arXiv:2301.13408>.
Maintained by Bouchra R. Nasri. Last updated 2 years ago.
3.8 match 1.00 score
cpenn-usgs
HyMETT:Hydrologic Model Evaluation and Time-Series Tools
Facilitates the analysis and evaluation of hydrologic model output and time-series data with functions focused on comparison of modeled (simulated) and observed data, period-of-record statistics, and trends.
Maintained by Colin Penn. Last updated 7 months ago.
1.7 match 2.00 score
lbosshard
scROSHI:Robust Supervised Hierarchical Identification of Single Cells
Identifying cell types based on expression profiles is a pillar of single cell analysis. 'scROSHI' identifies cell types based on expression profiles of single cell analysis by utilizing previously obtained cell type specific gene sets. It takes into account the hierarchical nature of cell type relationship and does not require training or annotated data. A detailed description of the method can be found at: Prummer, Bertolini, Bosshard, Barkmann, Yates, Boeva, The Tumor Profiler Consortium, Stekhoven, and Singer (2022) <doi:10.1101/2022.04.05.487176>.
Maintained by Lars Bosshard. Last updated 2 years ago.
2.0 match 1.70 score 9 scripts
mattansb
MSBMisc:Some functions I wrote that I find useful
misc. functions.
Maintained by Mattan S. Ben-Shachar. Last updated 2 years ago.
1.8 match 1 stars 1.70 score 2 scripts
edelmand21
dcortools:Providing Fast and Flexible Functions for Distance Correlation Analysis
Provides methods for distance covariance and distance correlation (Szekely, et al. (2007) <doi:10.1214/009053607000000505>), generalized version thereof (Sejdinovic, et al. (2013) <doi:10.1214/13-AOS1140>) and corresponding tests (Berschneider, Bottcher (2018) <arXiv:1808.07280>. Distance standard deviation methods (Edelmann, et al. (2020) <doi:10.1214/19-AOS1935>) and distance correlation methods for survival endpoints (Edelmann, et al. (2021) <doi:10.1111/biom.13470>) are also included.
Maintained by Dominic Edelmann. Last updated 2 years ago.
1.6 match 1.70 score
tnagler
wdm:Weighted Dependence Measures
Provides efficient implementations of weighted dependence measures and related asymptotic tests for independence. Implemented measures are the Pearson correlation, Spearman's rho, Kendall's tau, Blomqvist's beta, and Hoeffding's D; see, e.g., Nelsen (2006) <doi:10.1007/0-387-28678-0> and Hollander et al. (2015, ISBN:9780470387375).
Maintained by Thomas Nagler. Last updated 2 months ago.
0.5 match 3 stars 5.30 score 11 scripts 21 dependentscran
trend:Non-Parametric Trend Tests and Change-Point Detection
The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.
Maintained by Thorsten Pohlert. Last updated 1 years ago.
0.5 match 3 stars 5.31 score 9 dependents
orange-opensource
linkspotter:Bivariate Correlations Calculation and Visualization
Compute and visualize using the 'visNetwork' package all the bivariate correlations of a dataframe. Several and different types of correlation coefficients (Pearson's r, Spearman's rho, Kendall's tau, distance correlation, maximal information coefficient and equal-freq discretization-based maximal normalized mutual information) are used according to the variable couple type (quantitative vs categorical, quantitative vs quantitative, categorical vs categorical).
Maintained by Alassane Samba. Last updated 1 years ago.
0.5 match 7 stars 4.89 score 22 scriptsbioc
RCSL:Rank Constrained Similarity Learning for single cell RNA sequencing data
A novel clustering algorithm and toolkit RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both lo-cal similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearman’s rank correlations of a cell’s expression vector with those of other cells to measure its global similar-ity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similar-ity of a cell to other cells is a linear combination of its global similarity and local similarity.
Maintained by Qinglin Mei. Last updated 5 months ago.
singlecellsoftwareclusteringdimensionreductionrnaseqvisualizationsequencing
0.5 match 2 stars 4.48 score 10 scriptscran
HMMcopula:Markov Regime Switching Copula Models Estimation and Goodness-of-Fit
Estimation procedures and goodness-of-fit test for several Markov regime switching models and mixtures of bivariate copula models. The goodness-of-fit test is based on a Cramer-von Mises statistic and uses Rosenblatt's transform and parametric bootstrap to estimate the p-value. The proposed methodologies are described in Nasri, Remillard and Thioub (2020) <doi:10.1002/cjs.11534>.
Maintained by Bruno N Remillard. Last updated 5 months ago.
2.3 match 1 stars 1.00 score
daviden1013
testforDEP:Dependence Tests for Two Variables
Provides test statistics, p-value, and confidence intervals based on 9 hypothesis tests for dependence.
Maintained by En-shuo Hsu. Last updated 8 years ago.
2.0 match 1.00 score 7 scripts
vonnwalter23
MVisAGe:Compute and Visualize Bivariate Associations
Pearson and Spearman correlation coefficients are commonly used to quantify the strength of bivariate associations of genomic variables. For example, correlations of gene-level DNA copy number and gene expression measurements may be used to assess the impact of DNA copy number changes on gene expression in tumor tissue. 'MVisAGe' enables users to quickly compute and visualize the correlations in order to assess the effect of regional genomic events such as changes in DNA copy number or DNA methylation level. Please see Walter V, Du Y, Danilova L, Hayward MC, Hayes DN, 2018. Cancer Research <doi:10.1158/0008-5472.CAN-17-3464>.
Maintained by Vonn Walter. Last updated 7 years ago.
0.5 match 2.74 score 11 scripts
courtiol
timevarcorr:Time Varying Correlation
Computes how the correlation between 2 time-series changes over time. To do so, the package follows the method from Choi & Shin (2021) <doi:10.1007/s42952-020-00073-6>. It performs a non-parametric kernel smoothing (using a common bandwidth) of all underlying components required for the computation of a correlation coefficient (i.e., x, y, x^2, y^2, xy). An automatic selection procedure for the bandwidth parameter is implemented. Alternative kernels can be used (Epanechnikov, box and normal). Both Pearson and Spearman correlation coefficients can be estimated and change in correlation over time can be tested.
Maintained by Alexandre Courtiol. Last updated 1 years ago.
0.5 match 1 stars 2.70 score 5 scripts
melinar
ZIprop:Permutations Tests and Performance Indicator for Zero-Inflated Proportions Response
Permutations tests to identify factor correlated to zero-inflated proportions response. Provide a performance indicator based on Spearman correlation to quantify the part of correlation explained by the selected set of factors. See details for the method at the following preprint e.g.: <https://hal.archives-ouvertes.fr/hal-02936779v3>.
Maintained by Melina Ribaud. Last updated 4 years ago.
0.5 match 2.08 score 12 scripts
cran
rankdist:Distance Based Ranking Models
Implements distance based probability models for ranking data. The supported distance metrics include Kendall distance, Spearman distance, Footrule distance, Hamming distance, Weighted-tau distance and Weighted Kendall distance. Phi-component model and mixture models are also supported.
Maintained by Zhaozhi Qian. Last updated 6 years ago.
0.5 match 1.48 score 1 dependents
tuwhydro
corTESTsrd:Significance Testing of Rank Cross-Correlations under SRD
Significance test of Spearman's Rho or Kendall's Tau between short-range dependent random variables.
Maintained by David Lun. Last updated 2 years ago.
0.5 match 1.00 scorecran
PermCor:Robust Permutation Tests of Correlation Coefficients
Provides tools for statistical testing of correlation coefficients through robust permutation method and large sample approximation method. Tailored to different types of correlation coefficients including Pearson correlation coefficient, weighted Pearson correlation coefficient, Spearman correlation coefficient, and Lin's concordance correlation coefficient.The robust permutation test controls type I error under general scenarios when sample size is small and two variables are dependent but uncorrelated. The large sample approximation test generally controls type I error when the sample size is large (>200).
Maintained by Mengyu Fang. Last updated 7 months ago.
0.5 match 1.00 score
