Showing 200 of total 943 results (show query)
jrnold
ggthemes:Extra Themes, Scales and Geoms for 'ggplot2'
Some extra themes, geoms, and scales for 'ggplot2'. Provides 'ggplot2' themes and scales that replicate the look of plots by Edward Tufte, Stephen Few, 'Fivethirtyeight', 'The Economist', 'Stata', 'Excel', and 'The Wall Street Journal', among others. Provides 'geoms' for Tufte's box plot and range frame.
Maintained by Jeffrey B. Arnold. Last updated 1 years ago.
data-visualisationggplot2ggplot2-themesplotplottingthemevisualization
42.0 match 1.3k stars 16.17 score 40k scripts 102 dependents
r-lib
scales:Scale Functions for Visualization
Graphical scales map data to aesthetics, and provide methods for automatically determining breaks and labels for axes and legends.
Maintained by Thomas Lin Pedersen. Last updated 5 months ago.
17.6 match 419 stars 19.88 score 88k scripts 7.9k dependents
kkholst
mets:Analysis of Multivariate Event Times
Implementation of various statistical models for multivariate event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>. Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray, Ghosh-Lin, Binomial regression) with fast computation of influence functions.
Maintained by Klaus K. Holst. Last updated 2 days ago.
multivariate-time-to-eventsurvival-analysistime-to-eventfortranopenblascpp
24.5 match 14 stars 13.47 score 236 scripts 42 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 5 hours ago.
18.5 match 210 stars 17.61 score 17k scripts 750 dependents
santagos
dad:Three-Way / Multigroup Data Analysis Through Densities
The data consist of a set of variables measured on several groups of individuals. To each group is associated an estimated probability density function. The package provides tools to create or manage such data and functional methods (principal component analysis, multidimensional scaling, cluster analysis, discriminant analysis...) for such probability densities.
Maintained by Pierre Santagostini. Last updated 4 months ago.
52.6 match 5.33 score 92 scripts
cran
discretization:Data Preprocessing, Discretization for Classification
A collection of supervised discretization algorithms. It can also be grouped in terms of top-down or bottom-up, implementing the discretization algorithms.
Maintained by HyunJi Kim. Last updated 3 years ago.
90.1 match 3 stars 2.80 score 5 dependents
tidyverse
ggplot2:Create Elegant Data Visualisations Using the Grammar of Graphics
A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
Maintained by Thomas Lin Pedersen. Last updated 9 days ago.
data-visualisationvisualisation
9.7 match 6.6k stars 25.10 score 645k scripts 7.5k dependents
rikenbit
dcTensor:Discrete Matrix/Tensor Decomposition
Semi-Binary and Semi-Ternary Matrix Decomposition are performed based on Non-negative Matrix Factorization (NMF) and Singular Value Decomposition (SVD). For the details of the methods, see the reference section of GitHub README.md <https://github.com/rikenbit/dcTensor>.
Maintained by Koki Tsuyuzaki. Last updated 10 months ago.
42.1 match 3 stars 5.08 score
bjw34032
waveslim:Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing
Basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All figures in chapters 4-7 of GSW (2001) are reproducible using this package and R code available at the book website(s) below.
Maintained by Brandon Whitcher. Last updated 10 months ago.
26.4 match 3 stars 7.88 score 108 scripts 23 dependents
bayesball
LearnBayes:Learning Bayesian Inference
Contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.
Maintained by Jim Albert. Last updated 7 years ago.
18.0 match 38 stars 11.34 score 690 scripts 31 dependents
emilhvitfeldt
paletteer:Comprehensive Collection of Color Palettes
The choices of color palettes in R can be quite overwhelming with palettes spread over many packages with many different API's. This packages aims to collect all color palettes across the R ecosystem under the same package with a streamlined API.
Maintained by Emil Hvitfeldt. Last updated 9 months ago.
14.8 match 957 stars 13.50 score 6.9k scripts 23 dependents
r-simmer
simmer:Discrete-Event Simulation for R
A process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R. It is designed as a generic yet powerful framework. The architecture encloses a robust and fast simulation core written in 'C++' with automatic monitoring capabilities. It provides a rich and flexible R API that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type. Documentation about 'simmer' is provided by several vignettes included in this package, via the paper by Ucar, Smeets & Azcorra (2019, <doi:10.18637/jss.v090.i02>), and the paper by Ucar, Hernández, Serrano & Azcorra (2018, <doi:10.1109/MCOM.2018.1700960>); see 'citation("simmer")' for details.
Maintained by Iñaki Ucar. Last updated 6 months ago.
15.9 match 223 stars 11.47 score 440 scripts 6 dependents
disohda
DiscreteFDR:FDR Based Multiple Testing Procedures with Adaptation for Discrete Tests
Implementations of the multiple testing procedures for discrete tests described in the paper Döhler, Durand and Roquain (2018) "New FDR bounds for discrete and heterogeneous tests" <doi:10.1214/18-EJS1441>. The main procedures of the paper (HSU and HSD), their adaptive counterparts (AHSU and AHSD), and the HBR variant are available and are coded to take as input the results of a test procedure from package 'DiscreteTests', or a set of observed p-values and their discrete support under their nulls. A shortcut function to obtain such p-values and supports is also provided, along with a wrapper allowing to apply discrete procedures directly to data.
Maintained by Florian Junge. Last updated 6 days ago.
30.3 match 3 stars 6.02 score 16 scripts 2 dependents
gjmvanboxtel
gsignal:Signal Processing
R implementation of the 'Octave' package 'signal', containing a variety of signal processing tools, such as signal generation and measurement, correlation and convolution, filtering, filter design, filter analysis and conversion, power spectrum analysis, system identification, decimation and sample rate change, and windowing.
Maintained by Geert van Boxtel. Last updated 2 months ago.
16.9 match 24 stars 10.03 score 133 scripts 34 dependents
kylecaudle
rTensor2:MultiLinear Algebra
A set of tools for basic tensor operators. A tensor in the context of data analysis in a multidimensional array. The tools in this package rely on using any discrete transformation (e.g. Fast Fourier Transform (FFT)). Standard tools included are the Eigenvalue decomposition of a tensor, the QR decomposition and LU decomposition. Other functionality includes the inverse of a tensor and the transpose of a symmetric tensor. Functionality in the package is outlined in Kernfeld et al. (2015) <https://www.sciencedirect.com/science/article/pii/S0024379515004358>.
Maintained by Kyle Caudle. Last updated 12 months ago.
67.0 match 2.48 score 2 scripts 1 dependents
stscl
gdverse:Analysis of Spatial Stratified Heterogeneity
Analyzing spatial factors and exploring spatial associations based on the concept of spatial stratified heterogeneity, while also taking into account local spatial dependencies, spatial interpretability, complex spatial interactions, and robust spatial stratification. Additionally, it supports the spatial stratified heterogeneity family established in academic literature.
Maintained by Wenbo Lv. Last updated 2 days ago.
geographical-detectorgeoinformaticsgeospatial-analysisspatial-statisticsspatial-stratified-heterogeneitycpp
16.9 match 32 stars 9.07 score 41 scripts 2 dependents
spedygiorgio
markovchain:Easy Handling Discrete Time Markov Chains
Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>. Some functions for continuous times Markov chains depend on the suggested ctmcd package.
Maintained by Giorgio Alfredo Spedicato. Last updated 4 months ago.
ctmcdtmcmarkov-chainmarkov-modelr-programmingrcppopenblascpp
11.5 match 104 stars 12.78 score 712 scripts 4 dependents
r-barnes
dggridR:Discrete Global Grids
Spatial analyses involving binning require that every bin have the same area, but this is impossible using a rectangular grid laid over the Earth or over any projection of the Earth. Discrete global grids use hexagons, triangles, and diamonds to overcome this issue, overlaying the Earth with equally-sized bins. This package provides utilities for working with discrete global grids, along with utilities to aid in plotting such data.
Maintained by Sebastian Krantz. Last updated 6 months ago.
discrete-global-gridsgeospatialspatial-analysiscpp
15.5 match 168 stars 9.37 score 388 scripts 1 dependents
hrbrmstr
hrbrthemes:Additional Themes, Theme Components and Utilities for 'ggplot2'
A compilation of extra 'ggplot2' themes, scales and utilities, including a spell check function for plot label fields and an overall emphasis on typography. A copy of the 'Google' font 'Roboto Condensed' is also included.
Maintained by Bob Rudis. Last updated 2 days ago.
data-visualizationdatavisualizationggplot-extensionggplot2ggplot2-scalesggplot2-themesvisualization
10.3 match 1.3k stars 13.92 score 13k scripts 15 dependents
fabrice-rossi
mixvlmc:Variable Length Markov Chains with Covariates
Estimates Variable Length Markov Chains (VLMC) models and VLMC with covariates models from discrete sequences. Supports model selection via information criteria and simulation of new sequences from an estimated model. See Bühlmann, P. and Wyner, A. J. (1999) <doi:10.1214/aos/1018031204> for VLMC and Zanin Zambom, A., Kim, S. and Lopes Garcia, N. (2022) <doi:10.1111/jtsa.12615> for VLMC with covariates.
Maintained by Fabrice Rossi. Last updated 10 months ago.
machine-learningmarkov-chainmarkov-modelstatisticstime-seriescpp
21.8 match 2 stars 6.23 score 20 scripts
tidymodels
recipes:Preprocessing and Feature Engineering Steps for Modeling
A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.
Maintained by Max Kuhn. Last updated 6 days ago.
7.0 match 584 stars 18.71 score 7.2k scripts 380 dependentsdisohda
FDX:False Discovery Exceedance Controlling Multiple Testing Procedures
Multiple testing procedures for heterogeneous and discrete tests as described in Döhler and Roquain (2020) <doi:10.1214/20-EJS1771>. The main algorithms of the paper are available as continuous, discrete and weighted versions. They take as input the results of a test procedure from package 'DiscreteTests', or a set of observed p-values and their discrete support under their nulls. A shortcut function to obtain such p-values and supports is also provided, along with wrappers allowing to apply discrete procedures directly to data.
Maintained by Florian Junge. Last updated 4 months ago.
41.1 match 2 stars 3.15 score 1 scripts
mi2-warsaw
FSelectorRcpp:'Rcpp' Implementation of 'FSelector' Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support
'Rcpp' (free of 'Java'/'Weka') implementation of 'FSelector' entropy-based feature selection algorithms based on an MDL discretization (Fayyad U. M., Irani K. B.: Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. In 13'th International Joint Conference on Uncertainly in Artificial Intelligence (IJCAI93), pages 1022-1029, Chambery, France, 1993.) <https://www.ijcai.org/Proceedings/93-2/Papers/022.pdf> with a sparse matrix support.
Maintained by Zygmunt Zawadzki. Last updated 6 months ago.
entropyfeature-selectionrcppsparse-matrixcpp
15.7 match 35 stars 8.15 score 78 scripts 1 dependents
klausvigo
phangorn:Phylogenetic Reconstruction and Analysis
Allows for estimation of phylogenetic trees and networks using Maximum Likelihood, Maximum Parsimony, distance methods and Hadamard conjugation (Schliep 2011). Offers methods for tree comparison, model selection and visualization of phylogenetic networks as described in Schliep et al. (2017).
Maintained by Klaus Schliep. Last updated 1 months ago.
softwaretechnologyqualitycontrolphylogenetic-analysisphylogeneticsopenblascpp
7.6 match 206 stars 16.69 score 2.5k scripts 135 dependents
benjaminschlegel
glm.predict:Predicted Values and Discrete Changes for Regression Models
Functions to calculate predicted values and the difference between the two cases with confidence interval for lm() [linear model], glm() [generalized linear model], glm.nb() [negative binomial model], polr() [ordinal logistic model], vglm() [generalized ordinal logistic model], multinom() [multinomial model], tobit() [tobit model], svyglm() [survey-weighted generalised linear models] and lmer() [linear multilevel models] using Monte Carlo simulations or bootstrap. Reference: Bennet A. Zelner (2009) <doi:10.1002/smj.783>.
Maintained by Benjamin E. Schlegel. Last updated 7 months ago.
25.0 match 1 stars 5.10 score 55 scripts
twolodzko
extraDistr:Additional Univariate and Multivariate Distributions
Density, distribution function, quantile function and random generation for a number of univariate and multivariate distributions. This package implements the following distributions: Bernoulli, beta-binomial, beta-negative binomial, beta prime, Bhattacharjee, Birnbaum-Saunders, bivariate normal, bivariate Poisson, categorical, Dirichlet, Dirichlet-multinomial, discrete gamma, discrete Laplace, discrete normal, discrete uniform, discrete Weibull, Frechet, gamma-Poisson, generalized extreme value, Gompertz, generalized Pareto, Gumbel, half-Cauchy, half-normal, half-t, Huber density, inverse chi-squared, inverse-gamma, Kumaraswamy, Laplace, location-scale t, logarithmic, Lomax, multivariate hypergeometric, multinomial, negative hypergeometric, non-standard beta, normal mixture, Poisson mixture, Pareto, power, reparametrized beta, Rayleigh, shifted Gompertz, Skellam, slash, triangular, truncated binomial, truncated normal, truncated Poisson, Tukey lambda, Wald, zero-inflated binomial, zero-inflated negative binomial, zero-inflated Poisson.
Maintained by Tymoteusz Wolodzko. Last updated 11 days ago.
c-plus-plusc-plus-plus-11distributionmultivariate-distributionsprobabilityrandom-generationrcppstatisticscpp
10.9 match 53 stars 11.60 score 1.5k scripts 107 dependents
robindenz1
simDAG:Simulate Data from a DAG and Associated Node Information
Simulate complex data from a given directed acyclic graph and information about each individual node. Root nodes are simply sampled from the specified distribution. Child Nodes are simulated according to one of many implemented regressions, such as logistic regression, linear regression, poisson regression and more. Also includes a comprehensive framework for discrete-time simulation, which can generate even more complex longitudinal data.
Maintained by Robin Denz. Last updated 21 days ago.
causal-inferencedirected-acyclic-graphsimulation
15.9 match 10 stars 7.55 score 77 scripts
predictiveecology
SpaDES.core:Core Utilities for Developing and Running Spatially Explicit Discrete Event Models
Provides the core framework for a discrete event system to implement a complete data-to-decisions, reproducible workflow. The core components facilitate the development of modular pieces, and enable the user to include additional functionality by running user-built modules. Includes conditional scheduling, restart after interruption, packaging of reusable modules, tools for developing arbitrary automated workflows, automated interweaving of modules of different temporal resolution, and tools for visualizing and understanding the within-project dependencies. The suggested package 'NLMR' can be installed from the repository (<https://PredictiveEcology.r-universe.dev>).
Maintained by Eliot J B McIntire. Last updated 19 days ago.
discrete-events-simulationssimulation-frameworksimulation-modeling
11.2 match 10 stars 10.61 score 142 scripts 6 dependents
vdorie
dbarts:Discrete Bayesian Additive Regression Trees Sampler
Fits Bayesian additive regression trees (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) while allowing the updating of predictors or response so that BART can be incorporated as a conditional model in a Gibbs/Metropolis-Hastings sampler. Also serves as a drop-in replacement for package 'BayesTree'.
Maintained by Vincent Dorie. Last updated 12 days ago.
9.8 match 56 stars 10.96 score 418 scripts 14 dependentskylecaudle
TensorTools:Multilinear Algebra
A set of tools for basic tensor operators. A tensor in the context of data analysis in a multidimensional array. The tools in this package rely on using any discrete transformation (e.g. Fast Fourier Transform (FFT)). Standard tools included are the Eigenvalue decomposition of a tensor, the QR decomposition and LU decomposition. Other functionality includes the inverse of a tensor and the transpose of a symmetric tensor. Functionality in the package is outlined in Kernfeld, E., Kilmer, M., and Aeron, S. (2015) <doi:10.1016/j.laa.2015.07.021>.
Maintained by Kyle Caudle. Last updated 5 months ago.
52.6 match 2.00 score
vigou3
actuar:Actuarial Functions and Heavy Tailed Distributions
Functions and data sets for actuarial science: modeling of loss distributions; risk theory and ruin theory; simulation of compound models, discrete mixtures and compound hierarchical models; credibility theory. Support for many additional probability distributions to model insurance loss size and frequency: 23 continuous heavy tailed distributions; the Poisson-inverse Gaussian discrete distribution; zero-truncated and zero-modified extensions of the standard discrete distributions. Support for phase-type distributions commonly used to compute ruin probabilities. Main reference: <doi:10.18637/jss.v025.i07>. Implementation of the Feller-Pareto family of distributions: <doi:10.18637/jss.v103.i06>.
Maintained by Vincent Goulet. Last updated 2 months ago.
11.0 match 12 stars 9.44 score 732 scripts 35 dependentscran
wavethresh:Wavelets Statistics and Transforms
Performs 1, 2 and 3D real and complex-valued wavelet transforms, nondecimated transforms, wavelet packet transforms, nondecimated wavelet packet transforms, multiple wavelet transforms, complex-valued wavelet transforms, wavelet shrinkage for various kinds of data, locally stationary wavelet time series, nonstationary multiscale transfer function modeling, density estimation.
Maintained by Guy Nason. Last updated 7 months ago.
17.5 match 5.89 score 41 dependents
traets
idefix:Efficient Designs for Discrete Choice Experiments
Generates efficient designs for discrete choice experiments based on the multinomial logit model, and individually adapted designs for the mixed multinomial logit model. The generated designs can be presented on screen and choice data can be gathered using a shiny application. Traets F, Sanchez G, and Vandebroek M (2020) <doi:10.18637/jss.v096.i03>.
Maintained by Frits Traets. Last updated 3 years ago.
22.4 match 21 stars 4.47 score 21 scripts 2 dependents
jmotif
jmotif:Time Series Analysis Toolkit Based on Symbolic Aggregate Discretization, i.e. SAX
Implements time series z-normalization, SAX, HOT-SAX, VSM, SAX-VSM, RePair, and RRA algorithms facilitating time series motif (i.e., recurrent pattern), discord (i.e., anomaly), and characteristic pattern discovery along with interpretable time series classification.
Maintained by Pavel Senin. Last updated 2 years ago.
anomalydiscoverydiscorddiscretizationkddsaxsax-vsmtimeseriescpp
19.3 match 55 stars 5.12 score 48 scripts
fhernanb
DiscreteDists:Discrete Statistical Distributions
Implementation of new discrete statistical distributions. Each distribution includes the traditional functions as well as an additional function called the family function, which can be used to estimate parameters within the 'gamlss' framework.
Maintained by Freddy Hernandez-Barajas. Last updated 6 days ago.
24.8 match 3.81 score 1 scripts
r-forge
distr:Object Oriented Implementation of Distributions
S4-classes and methods for distributions.
Maintained by Peter Ruckdeschel. Last updated 2 months ago.
10.6 match 8.84 score 327 scripts 32 dependents
thinhong
denim:Generate and Simulate Deterministic Discrete-Time Compartmental Models
R package to build and simulate deterministic discrete-time compartmental models that can be non-Markov. Length of stay in each compartment can be defined to follow a parametric distribution (d_exponential(), d_gamma(), d_weibull(), d_lognormal()) or a non-parametric distribution (nonparametric()). Other supported types of transition from one compartment to another includes fixed transition (constant()), multinomial (multinomial()), fixed transition probability (transprob()).
Maintained by Anh Phan. Last updated 6 days ago.
15.9 match 2 stars 5.82 score 8 scripts
squidlobster
castor:Efficient Phylogenetics on Large Trees
Efficient phylogenetic analyses on massive phylogenies comprising up to millions of tips. Functions include pruning, rerooting, calculation of most-recent common ancestors, calculating distances from the tree root and calculating pairwise distances. Calculation of phylogenetic signal and mean trait depth (trait conservatism), ancestral state reconstruction and hidden character prediction of discrete characters, simulating and fitting models of trait evolution, fitting and simulating diversification models, dating trees, comparing trees, and reading/writing trees in Newick format. Citation: Louca, Stilianos and Doebeli, Michael (2017) <doi:10.1093/bioinformatics/btx701>.
Maintained by Stilianos Louca. Last updated 4 months ago.
16.0 match 2 stars 5.75 score 450 scripts 9 dependents
janusza
RoughSets:Data Analysis Using Rough Set and Fuzzy Rough Set Theories
Implementations of algorithms for data analysis based on the rough set theory (RST) and the fuzzy rough set theory (FRST). We not only provide implementations for the basic concepts of RST and FRST but also popular algorithms that derive from those theories. The methods included in the package can be divided into several categories based on their functionality: discretization, feature selection, instance selection, rule induction and classification based on nearest neighbors. RST was introduced by Zdzisław Pawlak in 1982 as a sophisticated mathematical tool to model and process imprecise or incomplete information. By using the indiscernibility relation for objects/instances, RST does not require additional parameters to analyze the data. FRST is an extension of RST. The FRST combines concepts of vagueness and indiscernibility that are expressed with fuzzy sets (as proposed by Zadeh, in 1965) and RST.
Maintained by Christoph Bergmeir. Last updated 5 years ago.
15.4 match 37 stars 5.61 score 185 scripts
colinfay
attempt:Tools for Defensive Programming
Tools for defensive programming, inspired by 'purrr' mappers and based on 'rlang'.'attempt' extends and facilitates defensive programming by providing a consistent grammar, and provides a set of easy to use functions for common tests and conditions. 'attempt' only depends on 'rlang', and focuses on speed, so it can be easily integrated in other functions and used in data analysis.
Maintained by Colin Fay. Last updated 7 months ago.
7.3 match 126 stars 11.57 score 101 scripts 86 dependents
boxuancui
DataExplorer:Automate Data Exploration and Treatment
Automated data exploration process for analytic tasks and predictive modeling, so that users could focus on understanding data and extracting insights. The package scans and analyzes each variable, and visualizes them with typical graphical techniques. Common data processing methods are also available to treat and format data.
Maintained by Boxuan Cui. Last updated 1 years ago.
data-analysisdata-explorationdata-scienceedavisualization
7.3 match 519 stars 11.16 score 2.2k scripts
suyusung
arm:Data Analysis Using Regression and Multilevel/Hierarchical Models
Functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.
Maintained by Yu-Sung Su. Last updated 5 months ago.
6.5 match 25 stars 12.38 score 3.3k scripts 89 dependents
clement-lee
crandep:Network Analysis of Dependencies of CRAN Packages
The dependencies of CRAN packages can be analysed in a network fashion. For each package we can obtain the packages that it depends, imports, suggests, etc. By iterating this procedure over a number of packages, we can build, visualise, and analyse the dependency network, enabling us to have a bird's-eye view of the CRAN ecosystem. One aspect of interest is the number of reverse dependencies of the packages, or equivalently the in-degree distribution of the dependency network. This can be fitted by the power law and/or an extreme value mixture distribution <doi:10.1111/stan.12355>, of which functions are provided.
Maintained by Clement Lee. Last updated 7 months ago.
12.8 match 8 stars 6.23 score 20 scripts
ralmond
CPTtools:Tools for Creating Conditional Probability Tables
Provides support parameterized tables for Bayesian networks, particularly the IRT-like DiBello tables. Also, provides some tools for visualing the networks.
Maintained by Russell Almond. Last updated 3 months ago.
15.1 match 1 stars 5.05 score 21 scripts 4 dependents
dsy109
tolerance:Statistical Tolerance Intervals and Regions
Statistical tolerance limits provide the limits between which we can expect to find a specified proportion of a sampled population with a given level of confidence. This package provides functions for estimating tolerance limits (intervals) for various univariate distributions (binomial, Cauchy, discrete Pareto, exponential, two-parameter exponential, extreme value, hypergeometric, Laplace, logistic, negative binomial, negative hypergeometric, normal, Pareto, Poisson-Lindley, Poisson, uniform, and Zipf-Mandelbrot), Bayesian normal tolerance limits, multivariate normal tolerance regions, nonparametric tolerance intervals, tolerance bands for regression settings (linear regression, nonlinear regression, nonparametric regression, and multivariate regression), and analysis of variance tolerance intervals. Visualizations are also available for most of these settings.
Maintained by Derek S. Young. Last updated 9 months ago.
11.4 match 4 stars 6.39 score 153 scripts 7 dependents
fgaspe04
discfrail:Cox Models for Time-to-Event Data with Nonparametric Discrete Group-Specific Frailties
Functions for fitting Cox proportional hazards models for grouped time-to-event data, where the shared group-specific frailties have a discrete nonparametric distribution. There are also functions for simulating from these models, and from similar models with a parametric baseline survival function.
Maintained by Francesca Gasperoni. Last updated 6 years ago.
24.2 match 1 stars 3.00 score 8 scripts
paternogbc
sensiPhy:Sensitivity Analysis for Comparative Methods
An implementation of sensitivity analysis for phylogenetic comparative methods. The package is an umbrella of statistical and graphical methods that estimate and report different types of uncertainty in PCM: (i) Species Sampling uncertainty (sample size; influential species and clades). (ii) Phylogenetic uncertainty (different topologies and/or branch lengths). (iii) Data uncertainty (intraspecific variation and measurement error).
Maintained by Gustavo Paterno. Last updated 5 years ago.
comparative-methodsecologyevolutionphylogeneticssensitivity-analysis
11.3 match 13 stars 6.38 score 61 scripts
ealdrich
wavelets:Functions for Computing Wavelet Filters, Wavelet Transforms and Multiresolution Analyses
Contains functions for computing and plotting discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transforms (MODWT), as well as their inverses. Additionally, it contains functionality for computing and plotting wavelet transform filters that are used in the above decompositions as well as multiresolution analyses.
Maintained by Eric Aldrich. Last updated 5 years ago.
14.5 match 4 stars 4.90 score 170 scripts 19 dependents
pablo14
funModeling:Exploratory Data Analysis and Data Preparation Tool-Box
Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book Data Science Live Book (<https://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.
Maintained by Pablo Casas. Last updated 2 years ago.
8.2 match 100 stars 8.57 score 654 scripts
trevorld
ggpattern:'ggplot2' Pattern Geoms
Provides 'ggplot2' geoms filled with various patterns. Includes a patterned version of every 'ggplot2' geom that has a region that can be filled with a pattern. Provides a suite of 'ggplot2' aesthetics and scales for controlling pattern appearances. Supports over a dozen builtin patterns (every pattern implemented by 'gridpattern') as well as allowing custom user-defined patterns.
Maintained by Trevor L. Davis. Last updated 2 months ago.
5.7 match 368 stars 12.33 score 1.7k scripts 3 dependents
paezha
discrtr:A Companion Package for the Book "Discrete Choice Analysis with 'R'"
Templates and data files to support "Discrete Choice Analysis with R", Páez, A. and Boisjoly, G. (2023) <doi:10.1007/978-3-031-20719-8>.
Maintained by Antonio Paez. Last updated 2 years ago.
discrete-choicediscrete-choice-data
17.5 match 3 stars 3.87 score 49 scripts
bioc
Informeasure:R implementation of information measures
This package consolidates a comprehensive set of information measurements, encompassing mutual information, conditional mutual information, interaction information, partial information decomposition, and part mutual information.
Maintained by Chu Pan. Last updated 5 months ago.
geneexpressionnetworkinferencenetworksoftware
15.1 match 3 stars 4.48 score 4 scriptsbioc
EnrichedHeatmap:Making Enriched Heatmaps
Enriched heatmap is a special type of heatmap which visualizes the enrichment of genomic signals on specific target regions. Here we implement enriched heatmap by ComplexHeatmap package. Since this type of heatmap is just a normal heatmap but with some special settings, with the functionality of ComplexHeatmap, it would be much easier to customize the heatmap as well as concatenating to a list of heatmaps to show correspondance between different data sources.
Maintained by Zuguang Gu. Last updated 5 months ago.
softwarevisualizationsequencinggenomeannotationcoveragecpp
6.2 match 190 stars 10.87 score 330 scripts 1 dependents
mjskay
ggdist:Visualizations of Distributions and Uncertainty
Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include but are not limited to: points with multiple uncertainty intervals, eye plots (Spiegelhalter D., 1999) <https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>, density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>, quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>, complementary cumulative distribution function barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>, and fit curves with multiple uncertainty ribbons.
Maintained by Matthew Kay. Last updated 4 months ago.
ggplot2uncertaintyuncertainty-visualizationvisualizationcpp
4.4 match 856 stars 15.24 score 3.1k scripts 61 dependents
thej022214
OUwie:Analysis of Evolutionary Rates in an OU Framework
Estimates rates for continuous character evolution under Brownian motion and a new set of Ornstein-Uhlenbeck based Hansen models that allow both the strength of the pull and stochastic motion to vary across selective regimes. Beaulieu et al (2012).
Maintained by Jeremy Beaulieu. Last updated 1 months ago.
7.8 match 9 stars 8.37 score 161 scripts
jpquast
ggplate:Create Layout Plots of Biological Culture Plates and Microplates
Enables users to create simple plots of biological culture plates as well as microplates. Both continuous and discrete values can be plotted onto the plate layout.
Maintained by Jan-Philipp Quast. Last updated 6 months ago.
11.3 match 94 stars 5.53 score 24 scripts
ambitiousbellydancingsquirrel
ggtea:Palettes and Themes for 'ggplot2'
A collection of palettes and themes for 'ggplot2', offering a light, pastel aesthetic. Syntax follows the 'viridis' package.
Maintained by Pushkar Sarkar. Last updated 3 years ago.
22.5 match 2.70 score
alexpghayes
distributions3:Probability Distributions as S3 Objects
Tools to create and manipulate probability distributions using S3. Generics pdf(), cdf(), quantile(), and random() provide replacements for base R's d/p/q/r style functions. Functions and arguments have been named carefully to minimize confusion for students in intro stats courses. The documentation for each distribution contains detailed mathematical notes.
Maintained by Alex Hayes. Last updated 6 months ago.
5.3 match 102 stars 11.35 score 118 scripts 7 dependents
csdaw
ggprism:A 'ggplot2' Extension Inspired by 'GraphPad Prism'
Provides various themes, palettes, and other functions that are used to customise ggplots to look like they were made in 'GraphPad Prism'. The 'Prism'-look is achieved with theme_prism() and scale_fill|colour_prism(), axes can be changed with custom guides like guide_prism_minor(), and significance indicators added with add_pvalue().
Maintained by Charlotte Dawson. Last updated 12 months ago.
5.6 match 175 stars 10.56 score 1.1k scripts 5 dependents
unuran
Runuran:R Interface to the 'UNU.RAN' Random Variate Generators
Interface to the 'UNU.RAN' library for Universal Non-Uniform RANdom variate generators. Thus it allows to build non-uniform random number generators from quite arbitrary distributions. In particular, it provides an algorithm for fast numerical inversion for distribution with given density function. In addition, the package contains densities, distribution functions and quantiles from a couple of distributions.
Maintained by Josef Leydold. Last updated 5 months ago.
8.6 match 6.87 score 180 scripts 8 dependents
ausgis
GD:Geographical Detectors for Assessing Spatial Factors
Geographical detectors for measuring spatial stratified heterogeneity, as described in Jinfeng Wang (2010) <doi:10.1080/13658810802443457> and Jinfeng Wang (2016) <doi:10.1016/j.ecolind.2016.02.052>. Includes the optimal discretization of continuous data, four primary functions of geographical detectors, comparison of size effects of spatial unit and the visualizations of results. To use the package and to refer the descriptions of the package, methods and case datasets, please cite Yongze Song (2020) <doi:10.1080/15481603.2020.1760434>. The model has been applied in factor exploration of road performance and multi-scale spatial segmentation for network data, as described in Yongze Song (2018) <doi:10.3390/rs10111696> and Yongze Song (2020) <doi:10.1109/TITS.2020.3001193>, respectively.
Maintained by Wenbo Lv. Last updated 4 months ago.
geographical-detectorspatial-stratified-heterogeneity
7.7 match 13 stars 7.49 score 51 scripts
amices
mice:Multivariate Imputation by Chained Equations
Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.
Maintained by Stef van Buuren. Last updated 6 days ago.
chained-equationsfcsimputationmicemissing-datamissing-valuesmultiple-imputationmultivariate-datacpp
3.5 match 462 stars 16.50 score 10k scripts 154 dependents
danheck
MCMCprecision:Precision of Discrete Parameters in Transdimensional MCMC
Estimates the precision of transdimensional Markov chain Monte Carlo (MCMC) output, which is often used for Bayesian analysis of models with different dimensionality (e.g., model selection). Transdimensional MCMC (e.g., reversible jump MCMC) relies on sampling a discrete model-indicator variable to estimate the posterior model probabilities. If only few switches occur between the models, precision may be low and assessment based on the assumption of independent samples misleading. Based on the observed transition matrix of the indicator variable, the method of Heck, Overstall, Gronau, & Wagenmakers (2019, Statistics & Computing, 29, 631-643) <doi:10.1007/s11222-018-9828-0> draws posterior samples of the stationary distribution to (a) assess the uncertainty in the estimated posterior model probabilities and (b) estimate the effective sample size of the MCMC output.
Maintained by Daniel W. Heck. Last updated 9 months ago.
10.5 match 5.49 score 52 scripts 4 dependents
mrc-ide
odin:ODE Generation and Integration
Generate systems of ordinary differential equations (ODE) and integrate them, using a domain specific language (DSL). The DSL uses R's syntax, but compiles to C in order to efficiently solve the system. A solver is not provided, but instead interfaces to the packages 'deSolve' and 'dde' are generated. With these, while solving the differential equations, no allocations are done and the calculations remain entirely in compiled code. Alternatively, a model can be transpiled to R for use in contexts where a C compiler is not present. After compilation, models can be inspected to return information about parameters and outputs, or intermediate values after calculations. 'odin' is not targeted at any particular domain and is suitable for any system that can be expressed primarily as mathematical expressions. Additional support is provided for working with delays (delay differential equations, DDE), using interpolated functions during interpolation, and for integrating quantities that represent arrays.
Maintained by Rich FitzJohn. Last updated 9 months ago.
5.9 match 106 stars 9.74 score 290 scripts 3 dependentscran
network:Classes for Relational Data
Tools to create and modify network objects. The network class can represent a range of relational data types, and supports arbitrary vertex/edge/graph attributes.
Maintained by Carter T. Butts. Last updated 3 months ago.
7.5 match 3 stars 7.65 score 146 dependents
ggobi
GGally:Extension to 'ggplot2'
The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.
Maintained by Barret Schloerke. Last updated 10 months ago.
3.5 match 597 stars 16.15 score 17k scripts 154 dependents
obrl-soil
h3jsr:Access Uber's H3 Library
Provides access to Uber's H3 library for geospatial indexing via its JavaScript transpile 'h3-js' <https://github.com/uber/h3-js> and 'V8' <https://github.com/jeroen/v8>.
Maintained by Lauren OBrien. Last updated 1 years ago.
discrete-global-gridsh3spatial-indexing
6.7 match 67 stars 8.39 score 205 scripts 4 dependents
hadley
plyr:Tools for Splitting, Applying and Combining Data
A set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to fit a model to each spatial location or time point in your study, summarise data by panels or collapse high-dimensional arrays to simpler summary statistics. The development of 'plyr' has been generously supported by 'Becton Dickinson'.
Maintained by Hadley Wickham. Last updated 4 months ago.
3.0 match 500 stars 18.16 score 83k scripts 3.3k dependents
urbaninstitute
urbnthemes:Additional theme and utilities for "ggplot2" in the Urban Institute style
Align "ggplot2" output more closely with the Urban Institute Data Visualization style guide <https://urbaninstitute.github.io/r-at-urban/graphics-guide.html>.
Maintained by Aaron R. Williams. Last updated 3 years ago.
10.1 match 79 stars 5.36 score 290 scripts
rivasiker
PhaseTypeR:General-Purpose Phase-Type Functions
General implementation of core function from phase-type theory. 'PhaseTypeR' can be used to model continuous and discrete phase-type distributions, both univariate and multivariate. The package includes functions for outputting the mean and (co)variance of phase-type distributions; their density, probability and quantile functions; functions for random draws; functions for reward-transformation; and functions for plotting the distributions as networks. For more information on these functions please refer to Bladt and Nielsen (2017, ISBN: 978-1-4939-8377-3) and Campillo Navarro (2019) <https://orbit.dtu.dk/en/publications/order-statistics-and-multivariate-discrete-phase-type-distributio>.
Maintained by Iker Rivas-González. Last updated 2 years ago.
10.0 match 2 stars 5.37 score 39 scripts
zhenkewu
baker:"Nested Partially Latent Class Models"
Provides functions to specify, fit and visualize nested partially-latent class models ( Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>; Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>; Wu and Chen (2021) <doi:10.1002/sim.8804>) for inference of population disease etiology and individual diagnosis. In the motivating Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities of interest sum to one hundred percent, the PERCH scientists frequently refer to them as population etiology pie and individual etiology pie, hence the name of the package.
Maintained by Zhenke Wu. Last updated 11 months ago.
bayesiancase-controllatent-class-analysisjagscpp
8.9 match 8 stars 6.00 score 21 scripts
albertofranzin
bnstruct:Bayesian Network Structure Learning from Data with Missing Values
Bayesian Network Structure Learning from Data with Missing Values. The package implements the Silander-Myllymaki complete search, the Max-Min Parents-and-Children, the Hill-Climbing, the Max-Min Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu, AIC, BIC. The package also implements methods for generating and using bootstrap samples, imputed data, inference.
Maintained by Alberto Franzin. Last updated 1 years ago.
9.5 match 1 stars 5.40 score 111 scripts 3 dependentsr-forge
distrEx:Extensions of Package 'distr'
Extends package 'distr' by functionals, distances, and conditional distributions.
Maintained by Matthias Kohl. Last updated 2 months ago.
7.6 match 6.68 score 107 scripts 17 dependents
pilaboratory
sads:Maximum Likelihood Models for Species Abundance Distributions
Maximum likelihood tools to fit and compare models of species abundance distributions and of species rank-abundance distributions.
Maintained by Paulo I. Prado. Last updated 1 years ago.
5.8 match 23 stars 8.66 score 244 scripts 3 dependents
collinerickson
comparer:Compare Output and Run Time
Quickly run experiments to compare the run time and output of code blocks. The function mbc() can make fast comparisons of code, and will calculate statistics comparing the resulting outputs. It can be used to compare model fits to the same data or see which function runs faster. The R6 class ffexp$new() runs a function using all possible combinations of selected inputs. This is useful for comparing the effect of different parameter values. It can also run in parallel and automatically save intermediate results, which is very useful for long computations.
Maintained by Collin Erickson. Last updated 5 months ago.
9.1 match 4 stars 5.38 score 20 scripts
allenzhuaz
MHTdiscrete:Multiple Hypotheses Testing for Discrete Data
A comprehensive tool for almost all existing multiple testing methods for discrete data. The package also provides some novel multiple testing procedures controlling FWER/FDR for discrete data. Given discrete p-values and their domains, the [method].p.adjust function returns adjusted p-values, which can be used to compare with the nominal significant level alpha and make decisions. For users' convenience, the functions also provide the output option for printing decision rules.
Maintained by Yalin Zhu. Last updated 6 years ago.
adjustment-computationsbenjamini-hochbergbonferronidiscrete-distributionsmultiple-testing-correction
14.9 match 1 stars 3.27 score 37 scripts
cumulocity-iot
pmml:Generate PMML for Various Models
The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define machine learning, statistical and data mining models and to share models between PMML compliant applications. More information about the PMML industry standard and the Data Mining Group can be found at <http://dmg.org/>. The generated PMML can be imported into any PMML consuming application, such as Zementis Predictive Analytics products. The package isofor (used for anomaly detection) can be installed with devtools::install_github("gravesee/isofor").
Maintained by Dmitriy Bolotov. Last updated 3 years ago.
6.1 match 20 stars 7.98 score 560 scripts 1 dependentsbioc
scMultiSim:Simulation of Multi-Modality Single Cell Data Guided By Gene Regulatory Networks and Cell-Cell Interactions
scMultiSim simulates paired single cell RNA-seq, single cell ATAC-seq and RNA velocity data, while incorporating mechanisms of gene regulatory networks, chromatin accessibility and cell-cell interactions. It allows users to tune various parameters controlling the amount of each biological factor, variation of gene-expression levels, the influence of chromatin accessibility on RNA sequence data, and so on. It can be used to benchmark various computational methods for single cell multi-omics data, and to assist in experimental design of wet-lab experiments.
Maintained by Hechen Li. Last updated 5 months ago.
singlecelltranscriptomicsgeneexpressionsequencingexperimentaldesign
6.8 match 23 stars 7.15 score 11 scripts
cbielow
PTXQC:Quality Report Generation for MaxQuant and mzTab Results
Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite (from .txt files) or mzTab files (ideally from OpenMS 'QualityControl' tool). Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) <doi:10.1021/acs.jproteome.5b00780>.
Maintained by Chris Bielow. Last updated 1 years ago.
drag-and-drophacktoberfestheatmapmatch-between-runsmaxquantmetricmztabopenmsproteomicsquality-controlquality-metricsreport
5.1 match 42 stars 9.35 score 105 scripts 1 dependents
teunbrand
ggh4x:Hacks for 'ggplot2'
A 'ggplot2' extension that does a variety of little helpful things. The package extends 'ggplot2' facets through customisation, by setting individual scales per panel, resizing panels and providing nested facets. Also allows multiple colour and fill scales per plot. Also hosts a smaller collection of stats, geoms and axis guides.
Maintained by Teun van den Brand. Last updated 3 months ago.
3.4 match 616 stars 13.98 score 4.4k scripts 20 dependentsdisohda
DiscreteTests:Vectorised Computation of P-Values and Their Supports for Several Discrete Statistical Tests
Provides vectorised functions for computing p-values of various common discrete statistical tests, as described e.g. in Agresti (2002) <doi:10.1002/0471249688>, including their distributions. Exact and approximate computation methods are provided. For exact p-values, several procedures of determining two-sided p-values are included, which are outlined in more detail in Hirji (2006) <doi:10.1201/9781420036190>.
Maintained by Florian Junge. Last updated 5 months ago.
10.5 match 4.45 score 35 scripts 3 dependents
slequime
nosoi:A Forward Agent-Based Transmission Chain Simulator
The aim of 'nosoi' (pronounced no.si) is to provide a flexible agent-based stochastic transmission chain/epidemic simulator (Lequime et al. Methods in Ecology and Evolution 11:1002-1007). It is named after the daimones of plague, sickness and disease that escaped Pandora's jar in the Greek mythology. 'nosoi' is able to take into account the influence of multiple variable on the transmission process (e.g. dual-host systems (such as arboviruses), within-host viral dynamics, transportation, population structure), alone or taken together, to create complex but relatively intuitive epidemiological simulations.
Maintained by Sebastian Lequime. Last updated 2 months ago.
6.4 match 8 stars 7.26 score 30 scriptsr-simmer
simmer.plot:Plotting Methods for 'simmer'
A set of plotting methods for 'simmer' trajectories and simulations.
Maintained by Iñaki Ucar. Last updated 5 months ago.
discrete-eventplotsimulationvisualization
7.5 match 10 stars 6.18 score 152 scripts
jwb133
smcfcs:Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
Implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.
Maintained by Jonathan Bartlett. Last updated 2 days ago.
5.1 match 11 stars 9.00 score 59 scripts 1 dependents
cran
mhsmm:Inference for Hidden Markov and Semi-Markov Models
Parameter estimation and prediction for hidden Markov and semi-Markov models for data with multiple observation sequences. Suitable for equidistant time series data, with multivariate and/or missing data. Allows user defined emission distributions.
Maintained by Jared OConnell. Last updated 2 years ago.
12.5 match 3 stars 3.56 score 2 dependents
luqqe
dtt:Discrete Trigonometric Transforms
This package provides functions for 1D and 2D Discrete Cosine Transform (DCT), Discrete Sine Transform (DST) and Discrete Hartley Transform (DHT).
Maintained by Lukasz Komsta. Last updated 18 years ago.
10.2 match 4.29 score 19 scripts 35 dependents
jedstephens
ExpertChoice:Design of Discrete Choice and Conjoint Analysis
Supports designing efficient discrete choice experiments (DCEs). Experimental designs can be formed on the basis of orthogonal arrays or search methods for optimal designs (Federov or mixed integer programs). Various methods for converting these experimental designs into a discrete choice experiment. Many efficiency measures! Draws from literature of Kuhfeld (2010) and Street et. al (2005) <doi:10.1016/j.ijresmar.2005.09.003>.
Maintained by Jed Stephens. Last updated 5 years ago.
9.0 match 15 stars 4.88 score 4 scripts
ghuiber
BTYD:Implementing BTYD Models with the Log Sum Exp Patch
Functions for data preparation, parameter estimation, scoring, and plotting for the BG/BB (Fader, Hardie, and Shang 2010 <doi:10.1287/mksc.1100.0580>), BG/NBD (Fader, Hardie, and Lee 2005 <doi:10.1287/mksc.1040.0098>) and Pareto/NBD and Gamma/Gamma (Fader, Hardie, and Lee 2005 <doi:10.1509/jmkr.2005.42.4.415>) models.
Maintained by Gabi Huiber. Last updated 3 years ago.
7.3 match 7 stars 6.03 score 103 scripts 1 dependents
mclements
microsimulation:Discrete Event Simulation in R and C++, with Tools for Cost-Effectiveness Analysis
Discrete event simulation using both R and C++ (Karlsson et al 2016; <doi:10.1109/eScience.2016.7870915>). The C++ code is adapted from the SSIM library <https://www.inf.usi.ch/carzaniga/ssim/>, allowing for event-oriented simulation. The code includes a SummaryReport class for reporting events and costs by age and other covariates. The C++ code is available as a static library for linking to other packages. A priority queue implementation is given in C++ together with an S3 closure and a reference class implementation. Finally, some tools are provided for cost-effectiveness analysis.
Maintained by Mark Clements. Last updated 7 months ago.
cppdiscrete-event-simulationhealth-economicsopenblascpp
10.0 match 38 stars 4.36 score 20 scriptsstscl
sdsfun:Spatial Data Science Complementary Features
Wrapping and supplementing commonly used functions in the R ecosystem related to spatial data science, while serving as a basis for other packages maintained by Wenbo Lv.
Maintained by Wenbo Lv. Last updated 15 days ago.
geoinformaticsspatial-data-analysisspatial-data-sciencespatial-statisticsopenblascppopenmp
6.5 match 16 stars 6.58 score 6 scripts 8 dependents
epiforecasts
scoringutils:Utilities for Scoring and Assessing Predictions
Facilitate the evaluation of forecasts in a convenient framework based on data.table. It allows user to to check their forecasts and diagnose issues, to visualise forecasts and missing data, to transform data before scoring, to handle missing forecasts, to aggregate scores, and to visualise the results of the evaluation. The package mostly focuses on the evaluation of probabilistic forecasts and allows evaluating several different forecast types and input formats. Find more information about the package in the Vignettes as well as in the accompanying paper, <doi:10.48550/arXiv.2205.07090>.
Maintained by Nikos Bosse. Last updated 13 days ago.
forecast-evaluationforecasting
3.8 match 52 stars 11.37 score 326 scripts 7 dependents
bnaras
ASSISTant:Adaptive Subgroup Selection in Group Sequential Trials
Clinical trial design for subgroup selection in three-stage group sequential trial. Includes facilities for design, exploration and analysis of such trials. An implementation of the initial DEFUSE-3 trial is also provided as a vignette.
Maintained by Balasubramanian Narasimhan. Last updated 5 years ago.
9.3 match 4.54 score 23 scriptsbioc
MAST:Model-based Analysis of Single Cell Transcriptomics
Methods and models for handling zero-inflated single cell assay data.
Maintained by Andrew McDavid. Last updated 5 months ago.
geneexpressiondifferentialexpressiongenesetenrichmentrnaseqtranscriptomicssinglecell
3.3 match 230 stars 12.75 score 1.8k scripts 5 dependentsbioc
POMA:Tools for Omics Data Analysis
The POMA package offers a comprehensive toolkit designed for omics data analysis, streamlining the process from initial visualization to final statistical analysis. Its primary goal is to simplify and unify the various steps involved in omics data processing, making it more accessible and manageable within a single, intuitive R package. Emphasizing on reproducibility and user-friendliness, POMA leverages the standardized SummarizedExperiment class from Bioconductor, ensuring seamless integration and compatibility with a wide array of Bioconductor tools. This approach guarantees maximum flexibility and replicability, making POMA an essential asset for researchers handling omics datasets. See https://github.com/pcastellanoescuder/POMAShiny. Paper: Castellano-Escuder et al. (2021) <doi:10.1371/journal.pcbi.1009148> for more details.
Maintained by Pol Castellano-Escuder. Last updated 4 months ago.
batcheffectclassificationclusteringdecisiontreedimensionreductionmultidimensionalscalingnormalizationpreprocessingprincipalcomponentregressionrnaseqsoftwarestatisticalmethodvisualizationbioconductorbioinformaticsdata-visualizationdimension-reductionexploratory-data-analysismachine-learningomics-data-integrationpipelinepre-processingstatistical-analysisuser-friendlyworkflow
5.1 match 11 stars 8.23 score 20 scripts 1 dependentsr-simmer
simmer.bricks:Helper Methods for 'simmer' Trajectories
Provides wrappers for common activity patterns in 'simmer' trajectories.
Maintained by Iñaki Ucar. Last updated 2 years ago.
7.5 match 6 stars 5.64 score 49 scripts 1 dependents
rpolars
polars:Lightning-Fast 'DataFrame' Library
Lightning-fast 'DataFrame' library written in 'Rust'. Convert R data to 'Polars' data and vice versa. Perform fast, lazy, larger-than-memory and optimized data queries. 'Polars' is interoperable with the package 'arrow', as both are based on the 'Apache Arrow' Columnar Format.
Maintained by Soren Welling. Last updated 3 days ago.
3.5 match 499 stars 12.01 score 1.0k scripts 2 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.
arulesassociation-rulesfrequent-itemsets
3.0 match 194 stars 13.99 score 3.3k scripts 28 dependents
leerichardson
swdft:Sliding Window Discrete Fourier Transform (SWDFT)
Implements the Sliding Window Discrete Fourier Transform (SWDFT). Also provides statistical methods based on the SWDFT, and graphical tools to display the outputs.
Maintained by Lee F. Richardson. Last updated 6 years ago.
15.5 match 1 stars 2.70 score 6 scripts
ninohardt
echoice2:Choice Models with Economic Foundation
Implements choice models based on economic theory, including estimation using Markov chain Monte Carlo (MCMC), prediction, and more. Its usability is inspired by ideas from 'tidyverse'. Models include versions of the Hierarchical Multinomial Logit and Multiple Discrete-Continous (Volumetric) models with and without screening. The foundations of these models are described in Allenby, Hardt and Rossi (2019) <doi:10.1016/bs.hem.2019.04.002>. Models with conjunctive screening are described in Kim, Hardt, Kim and Allenby (2022) <doi:10.1016/j.ijresmar.2022.04.001>. Models with set-size variation are described in Hardt and Kurz (2020) <doi:10.2139/ssrn.3418383>.
Maintained by Nino Hardt. Last updated 1 years ago.
choice-modelsopenblascppopenmp
10.3 match 1 stars 4.00 score 7 scripts
spsanderson
healthyR.ai:The Machine Learning and AI Modeling Companion to 'healthyR'
Hospital machine learning and ai data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative hospital data. Some of these include predicting length of stay, and readmits. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.
Maintained by Steven Sanderson. Last updated 2 months ago.
aiartificial-intelligencehealthcareanalyticshealthyrhealthyversemachine-learning
5.5 match 16 stars 7.37 score 36 scripts 1 dependents
loelschlaeger
RprobitB:Bayesian Probit Choice Modeling
Bayes estimation of probit choice models, both in the cross-sectional and panel setting. The package can analyze binary, multivariate, ordered, and ranked choices, as well as heterogeneity of choice behavior among deciders. The main functionality includes model fitting via Markov chain Monte Carlo m ethods, tools for convergence diagnostic, choice data simulation, in-sample and out-of-sample choice prediction, and model selection using information criteria and Bayes factors. The latent class model extension facilitates preference-based decider classification, where the number of latent classes can be inferred via the Dirichlet process or a weight-based updating heuristic. This allows for flexible modeling of choice behavior without the need to impose structural constraints. For a reference on the method see Oelschlaeger and Bauer (2021) <https://trid.trb.org/view/1759753>.
Maintained by Lennart Oelschläger. Last updated 5 months ago.
bayesdiscrete-choiceprobitopenblascppopenmp
7.5 match 4 stars 5.45 score 1 scriptsr-simmer
simmer.optim:Parameter Optimization Functions for 'simmer'
A set of optimization functions for variable optimization in simmer simulations.
Maintained by Bart Smeets. Last updated 2 years ago.
discrete-eventoptimizationsimulation
9.4 match 15 stars 4.35 score 4 scripts
kbhoehn
dowser:B Cell Receptor Phylogenetics Toolkit
Provides a set of functions for inferring, visualizing, and analyzing B cell phylogenetic trees. Provides methods to 1) reconstruct unmutated ancestral sequences, 2) build B cell phylogenetic trees using multiple methods, 3) visualize trees with metadata at the tips, 4) reconstruct intermediate sequences, 5) detect biased ancestor-descendant relationships among metadata types Workflow examples available at documentation site (see URL). Citations: Hoehn et al (2022) <doi:10.1371/journal.pcbi.1009885>, Hoehn et al (2021) <doi:10.1101/2021.01.06.425648>.
Maintained by Kenneth Hoehn. Last updated 2 months ago.
5.9 match 6.81 score 84 scripts
jhelvy
cbcTools:Choice-Based Conjoint Experiment Design Generation and Power Evaluation in R
Design and evaluate choice-based conjoint survey experiments. Generate a variety of survey designs, including random designs, full factorial designs, orthogonal designs, D-optimal designs, and Bayesian D-efficient designs as well as designs with "no choice" options and "labeled" (also known as "alternative specific") designs. Conveniently inspect the design balance and overlap, and simulate choice data for a survey design either randomly or according to a multinomial or mixed logit utility model defined by user-provided prior parameters. Conduct a power analysis for a given survey design by estimating the same model on different subsets of the data to simulate different sample sizes. Full factorial and orthogonal designs are obtained using the 'DoE.base' package (Grömping, 2018) <doi:10.18637/jss.v085.i05>. D-optimal designs are obtained using the 'AlgDesign' package (Wheeler, 2022) <https://CRAN.R-project.org/package=AlgDesign>. Bayesian D-efficient designs are obtained using the 'idefix' package (Traets et al, 2020) <doi:10.18637/jss.v096.i03>. Choice simulation and model estimation in power analyses are handled using the 'logitr' package (Helveston, 2023) <doi:10.18637/jss.v105.i10>.
Maintained by John Helveston. Last updated 1 years ago.
cbcconjointdesigndiscrete-choicesawtoothsurvey
7.5 match 6 stars 5.30 score 67 scripts
lbbe-software
fitdistrplus:Help to Fit of a Parametric Distribution to Non-Censored or Censored Data
Extends the fitdistr() function (of the MASS package) with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left censored, right censored and interval censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit estimation (MGE) and maximum spacing estimation (MSE) methods (available only for non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction to parametric estimation.
Maintained by Aurélie Siberchicot. Last updated 12 days ago.
2.5 match 54 stars 16.15 score 4.5k scripts 153 dependents
schaubert
catdata:Categorical Data
This R-package contains examples from the book "Regression for Categorical Data", Tutz 2012, Cambridge University Press. The names of the examples refer to the chapter and the data set that is used.
Maintained by Gunther Schauberger. Last updated 1 years ago.
6.0 match 6.61 score 158 scripts 2 dependents
pedersen-fisheries-lab
sspm:Spatial Surplus Production Model Framework for Northern Shrimp Populations
Implement a GAM-based (Generalized Additive Models) spatial surplus production model (spatial SPM), aimed at modeling northern shrimp population in Atlantic Canada but potentially to any stock in any location. The package is opinionated in its implementation of SPMs as it internally makes the choice to use penalized spatial gams with time lags. However, it also aims to provide options for the user to customize their model. The methods are described in Pedersen et al. (2022, <https://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2022/2022_062-eng.html>).
Maintained by Valentin Lucet. Last updated 1 months ago.
7.4 match 3 stars 5.28 score 21 scripts
aidangildea
duke:Creating a Color-Blind Friendly Duke Color Package
Generates visualizations with Duke’s official suite of colors in a color blind friendly way.
Maintained by Aidan Gildea. Last updated 1 years ago.
7.9 match 2 stars 4.88 score 15 scripts
animint
animint2:Animated Interactive Grammar of Graphics
Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.
Maintained by Toby Hocking. Last updated 27 days ago.
4.3 match 64 stars 8.87 score 173 scriptsr-forge
pcalg:Methods for Graphical Models and Causal Inference
Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.
Maintained by Markus Kalisch. Last updated 6 months ago.
5.1 match 7.32 score 700 scripts 19 dependents
reconhub
distcrete:Discrete Distribution Approximations
Creates discretised versions of continuous distribution functions by mapping continuous values to an underlying discrete grid, based on a (uniform) frequency of discretisation, a valid discretisation point, and an integration range. For a review of discretisation methods, see Chakraborty (2015) <doi:10.1186/s40488-015-0028-6>.
Maintained by Steph Locke. Last updated 7 years ago.
5.0 match 5 stars 7.49 score 152 scripts 9 dependents
alessandro-barbiero
GenOrd:Simulation of Discrete Random Variables with Given Correlation Matrix and Marginal Distributions
A gaussian copula based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.
Maintained by Alessandro Barbiero. Last updated 10 years ago.
10.5 match 2 stars 3.59 score 36 scripts 18 dependents
pauljohn32
rockchalk:Regression Estimation and Presentation
A collection of functions for interpretation and presentation of regression analysis. These functions are used to produce the statistics lectures in <https://pj.freefaculty.org/guides/>. Includes regression diagnostics, regression tables, and plots of interactions and "moderator" variables. The emphasis is on "mean-centered" and "residual-centered" predictors. The vignette 'rockchalk' offers a fairly comprehensive overview. The vignette 'Rstyle' has advice about coding in R. The package title 'rockchalk' refers to our school motto, 'Rock Chalk Jayhawk, Go K.U.'.
Maintained by Paul E. Johnson. Last updated 3 years ago.
5.2 match 7.13 score 584 scripts 18 dependentscran
stpm:Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes
Utilities to estimate parameters of the models with survival functions induced by stochastic covariates. Miscellaneous functions for data preparation and simulation are also provided. For more information, see: (i)"Stochastic model for analysis of longitudinal data on aging and mortality" by Yashin A. et al. (2007), Mathematical Biosciences, 208(2), 538-551, <DOI:10.1016/j.mbs.2006.11.006>; (ii) "Health decline, aging and mortality: how are they related?" by Yashin A. et al. (2007), Biogerontology 8(3), 291(302), <DOI:10.1007/s10522-006-9073-3>.
Maintained by Ilya Y. Zhbannikov. Last updated 3 years ago.
13.7 match 2.70 score
kelliejarcher
countgmifs:Discrete Response Regression for High-Dimensional Data
Provides a function for fitting Poisson and negative binomial regression models when the number of parameters exceeds the sample size, using the the generalized monotone incremental forward stagewise method.
Maintained by Kellie Archer. Last updated 3 years ago.
10.0 match 3.70 score 1 scripts
epinowcast
primarycensored:Primary Event Censored Distributions
Provides functions for working with primary event censored distributions and 'Stan' implementations for use in Bayesian modeling. Primary event censored distributions are useful for modeling delayed reporting scenarios in epidemiology and other fields (Charniga et al. (2024) <doi:10.48550/arXiv.2405.08841>). It also provides support for arbitrary delay distributions, a range of common primary distributions, and allows for truncation and secondary event censoring to be accounted for (Park et al. (2024) <doi:10.1101/2024.01.12.24301247>). A subset of common distributions also have analytical solutions implemented, allowing for faster computation. In addition, it provides multiple methods for fitting primary event censored distributions to data via optional dependencies.
Maintained by Sam Abbott. Last updated 1 months ago.
censoringdistributionsmc-stantruncation
4.8 match 8 stars 7.69 score 16 scripts 1 dependents
igraph
igraph:Network Analysis and Visualization
Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.
Maintained by Kirill Müller. Last updated 9 hours ago.
complex-networksgraph-algorithmsgraph-theorymathematicsnetwork-analysisnetwork-graphfortranlibxml2glpkopenblascpp
1.7 match 582 stars 21.11 score 31k scripts 1.9k dependentsstscl
sesp:Spatially Explicit Stratified Power
Assesses spatial associations between variables through an equivalent geographical detector (q-statistic) within a regression framework and incorporates a spatially explicit stratified power model by integrating spatial dependence and spatial stratified heterogeneity, facilitating the modeling of complex spatial relationships.
Maintained by Wenbo Lv. Last updated 2 months ago.
spatial-explicit-geographical-detectorspatial-stratified-heterogeneitycpp
6.7 match 15 stars 5.43 score
rmheiberger
HH:Statistical Analysis and Data Display: Heiberger and Holland
Support software for Statistical Analysis and Data Display (Second Edition, Springer, ISBN 978-1-4939-2121-8, 2015) and (First Edition, Springer, ISBN 0-387-40270-5, 2004) by Richard M. Heiberger and Burt Holland. This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The second edition includes redesigned graphics and additional chapters. The authors emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. All functions introduced in the book are in the package. R code for all examples, both graphs and tables, in the book is included in the scripts directory of the package.
Maintained by Richard M. Heiberger. Last updated 1 months ago.
5.6 match 3 stars 6.42 score 752 scripts 5 dependentsepiforecasts
EpiNow2:Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters
Estimates the time-varying reproduction number, rate of spread, and doubling time using a range of open-source tools (Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1>), and current best practices (Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is actively supported.
Maintained by Sebastian Funk. Last updated 25 days ago.
backcalculationcovid-19gaussian-processesopen-sourcereproduction-numberstancpp
3.0 match 120 stars 11.88 score 210 scripts
bmihaljevic
bnclassify:Learning Discrete Bayesian Network Classifiers from Data
State-of-the art algorithms for learning discrete Bayesian network classifiers from data, including a number of those described in Bielza & Larranaga (2014) <doi:10.1145/2576868>, with functions for prediction, model evaluation and inspection.
Maintained by Mihaljevic Bojan. Last updated 1 years ago.
5.2 match 18 stars 6.85 score 66 scriptsbioc
MOSim:Multi-Omics Simulation (MOSim)
MOSim package simulates multi-omic experiments that mimic regulatory mechanisms within the cell, allowing flexible experimental design including time course and multiple groups.
Maintained by Sonia Tarazona. Last updated 5 months ago.
softwaretimecourseexperimentaldesignrnaseqcpp
4.7 match 9 stars 7.46 score 11 scripts
goranbrostrom
eha:Event History Analysis
Parametric proportional hazards fitting with left truncation and right censoring for common families of distributions, piecewise constant hazards, and discrete models. Parametric accelerated failure time models for left truncated and right censored data. Proportional hazards models for tabular and register data. Sampling of risk sets in Cox regression, selections in the Lexis diagram, bootstrapping. Broström (2022) <doi:10.1201/9780429503764>.
Maintained by Göran Broström. Last updated 9 months ago.
3.6 match 7 stars 9.76 score 308 scripts 10 dependentstidymodels
embed:Extra Recipes for Encoding Predictors
Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models <doi:10.48550/arXiv.1611.09477> or nonlinear models <doi:10.48550/arXiv.1604.06737> can be used. There are also functions for dimension reduction and other approaches.
Maintained by Emil Hvitfeldt. Last updated 2 months ago.
3.8 match 142 stars 9.35 score 1.1k scriptscran
cdparcoord:Top Frequency-Based Parallel Coordinates
Parallel coordinate plotting with resolutions for large data sets and missing values.
Maintained by Norm Matloff. Last updated 6 years ago.
12.4 match 2.81 score 13 scripts
olink-proteomics
OlinkAnalyze:Facilitate Analysis of Proteomic Data from Olink
A collection of functions to facilitate analysis of proteomic data from Olink, primarily NPX data that has been exported from Olink Software. The functions also work on QUANT data from Olink by log- transforming the QUANT data. The functions are focused on reading data, facilitating data wrangling and quality control analysis, performing statistical analysis and generating figures to visualize the results of the statistical analysis. The goal of this package is to help users extract biological insights from proteomic data run on the Olink platform.
Maintained by Kathleen Nevola. Last updated 20 days ago.
olinkproteomicsproteomics-data-analysis
3.6 match 104 stars 9.72 score 61 scripts
johnswyou
fastWavelets:Compute Maximal Overlap Discrete Wavelet Transform (MODWT) and À Trous Discrete Wavelet Transform
A lightweight package to compute Maximal Overlap Discrete Wavelet Transform (MODWT) and À Trous Discrete Wavelet Transform by leveraging the power of 'Rcpp' to make these operations fast. This package was designed for use in forecasting, and allows users avoid the inclusion of future data when performing wavelet decomposition of time series. See Quilty and Adamowski (2018) <doi:10.1016/j.jhydrol.2018.05.003>.
Maintained by John You. Last updated 2 years ago.
10.6 match 4 stars 3.30 score 3 scripts
wolfgangrolke
Rgof:1d Goodness of Fit Tests
Routines that allow the user to run a large number of goodness-of-fit tests. It allows for data to be continuous or discrete. It includes routines to estimate the power of the tests and display them as a power graph. The routine run.studies allows a user to quickly study the power of a new method and how it compares to some of the standard ones.
Maintained by Wolfgang Rolke. Last updated 3 days ago.
13.4 match 2.60 score 4 scripts
alexanderrobitzsch
sirt:Supplementary Item Response Theory Models
Supplementary functions for item response models aiming to complement existing R packages. The functionality includes among others multidimensional compensatory and noncompensatory IRT models (Reckase, 2009, <doi:10.1007/978-0-387-89976-3>), MCMC for hierarchical IRT models and testlet models (Fox, 2010, <doi:10.1007/978-1-4419-0742-4>), NOHARM (McDonald, 1982, <doi:10.1177/014662168200600402>), Rasch copula model (Braeken, 2011, <doi:10.1007/s11336-010-9190-4>; Schroeders, Robitzsch & Schipolowski, 2014, <doi:10.1111/jedm.12054>), faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011, <doi:10.1111/j.1745-3984.2011.00143.x>), ordinal IRT model (ISOP; Scheiblechner, 1995, <doi:10.1007/BF02301417>), DETECT statistic (Stout, Habing, Douglas & Kim, 1996, <doi:10.1177/014662169602000403>), local structural equation modeling (LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016, <doi:10.1080/00273171.2016.1142856>).
Maintained by Alexander Robitzsch. Last updated 3 months ago.
item-response-theoryopenblascpp
3.5 match 23 stars 10.01 score 280 scripts 22 dependents
kliegr
arc:Association Rule Classification
Implements the Classification-based on Association Rules (CBA) algorithm for association rule classification. The package, also described in Hahsler et al. (2019) <doi:10.32614/RJ-2019-048>, contains several convenience methods that allow to automatically set CBA parameters (minimum confidence, minimum support) and it also natively handles numeric attributes by integrating a pre-discretization step. The rule generation phase is handled by the 'arules' package. To further decrease the size of the CBA models produced by the 'arc' package, postprocessing by the 'qCBA' package is suggested.
Maintained by Tomas Kliegr. Last updated 6 months ago.
6.8 match 7 stars 5.09 score 39 scripts 1 dependentscran
discSurv:Discrete Time Survival Analysis
Provides data transformations, estimation utilities, predictive evaluation measures and simulation functions for discrete time survival analysis.
Maintained by Thomas Welchowski. Last updated 3 years ago.
16.4 match 2 stars 2.11 score 64 scripts
philchalmers
mirt:Multidimensional Item Response Theory
Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.
Maintained by Phil Chalmers. Last updated 11 days ago.
2.3 match 210 stars 14.98 score 2.5k scripts 40 dependents
emmanuelparadis
ape:Analyses of Phylogenetics and Evolution
Functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, reading and writing nucleotide sequences as well as importing from BioConductor, and several tools such as Mantel's test, generalized skyline plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation of absolute evolutionary rates and clock-like trees using mean path lengths and penalized likelihood, dating trees with non-contemporaneous sequences, translating DNA into AA sequences, and assessing sequence alignments. Phylogeny estimation can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, Muscle) whose results are returned into R.
Maintained by Emmanuel Paradis. Last updated 10 hours ago.
2.0 match 64 stars 17.22 score 13k scripts 599 dependents
andyliaw-mrk
locfit:Local Regression, Likelihood and Density Estimation
Local regression, likelihood and density estimation methods as described in the 1999 book by Loader.
Maintained by Andy Liaw. Last updated 11 days ago.
3.6 match 1 stars 9.40 score 428 scripts 606 dependents
r-tmap
tmap:Thematic Maps
Thematic maps are geographical maps in which spatial data distributions are visualized. This package offers a flexible, layer-based, and easy to use approach to create thematic maps, such as choropleths and bubble maps.
Maintained by Martijn Tennekes. Last updated 4 days ago.
choropleth-mapsmapsspatialthematic-mapsvisualisation
2.0 match 880 stars 16.73 score 13k scripts 24 dependents
rbarkerclarke
gtexture:Generalized Application of Co-Occurrence Matrices and Haralick Texture
Generalizes application of gray-level co-occurrence matrix (GLCM) metrics to objects outside of images. The current focus is to apply GLCM metrics to the study of biological networks and fitness landscapes that are used in studying evolutionary medicine and biology, particularly the evolution of cancer resistance. The package was used in our publication, Barker-Clarke et al. (2023) <doi:10.1088/1361-6560/ace305>. A general reference to learn more about mathematical oncology can be found at Rockne et al. (2019) <doi:10.1088/1478-3975/ab1a09>.
Maintained by Rowan Barker-Clarke. Last updated 12 months ago.
11.1 match 3.00 score 1 scripts
stan-dev
bayesplot:Plotting for Bayesian Models
Plotting functions for posterior analysis, MCMC diagnostics, prior and posterior predictive checks, and other visualizations to support the applied Bayesian workflow advocated in Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) <doi:10.1111/rssa.12378>. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.
Maintained by Jonah Gabry. Last updated 1 months ago.
bayesianggplot2mcmcpandocstanstatistical-graphicsvisualization
2.0 match 436 stars 16.69 score 6.5k scripts 98 dependents
fcheysson
hawkesbow:Estimation of Hawkes Processes from Binned Observations
Implements an estimation method for Hawkes processes when count data are only observed in discrete time, using a spectral approach derived from the Bartlett spectrum, see Cheysson and Lang (2020) <arXiv:2003.04314>. Some general use functions for Hawkes processes are also included: simulation of (in)homogeneous Hawkes process, maximum likelihood estimation, residual analysis, etc.
Maintained by Felix Cheysson. Last updated 1 years ago.
7.3 match 7 stars 4.54 score 4 scriptsobrl-soil
mpspline2:Mass-Preserving Spline Functions for Soil Data
A low-dependency implementation of GSIF::mpspline() <https://r-forge.r-project.org/scm/viewvc.php/pkg/R/mpspline.R?view=markup&revision=240&root=gsif>, which applies a mass-preserving spline to soil attributes. Splining soil data is a safe way to make continuous down-profile estimates of attributes measured over discrete, often discontinuous depth intervals.
Maintained by Lauren OBrien. Last updated 1 years ago.
7.4 match 6 stars 4.50 score 35 scripts
xiangpin
ggstar:Multiple Geometric Shape Point Layer for 'ggplot2'
To create the multiple polygonal point layer for easily discernible shapes, we developed the package, it is like the 'geom_point' of 'ggplot2'. It can be used to draw the scatter plot.
Maintained by Shuangbin Xu. Last updated 11 months ago.
4.0 match 101 stars 8.22 score 282 scripts 3 dependents
furrer-lab
abn:Modelling Multivariate Data with Additive Bayesian Networks
The 'abn' R package facilitates Bayesian network analysis, a probabilistic graphical model that derives from empirical data a directed acyclic graph (DAG). This DAG describes the dependency structure between random variables. The R package 'abn' provides routines to help determine optimal Bayesian network models for a given data set. These models are used to identify statistical dependencies in messy, complex data. Their additive formulation is equivalent to multivariate generalised linear modelling, including mixed models with independent and identically distributed (iid) random effects. The core functionality of the 'abn' package revolves around model selection, also known as structure discovery. It supports both exact and heuristic structure learning algorithms and does not restrict the data distribution of parent-child combinations, providing flexibility in model creation and analysis. The 'abn' package uses Laplace approximations for metric estimation and includes wrappers to the 'INLA' package. It also employs 'JAGS' for data simulation purposes. For more resources and information, visit the 'abn' website.
Maintained by Matteo Delucchi. Last updated 5 days ago.
bayesian-networkbinomialcategorical-datagaussiangrouped-datasetsmixed-effectsmultinomialmultivariatepoissonstructure-learninggslopenblascppopenmpjags
4.7 match 6 stars 6.94 score 90 scripts
liuaber
CompPareto:Discrete Composite Distributions with Pareto Tails
The package contains basic functions for discrete composite distributions with Pareto tails.
Maintained by Bowen Liu. Last updated 1 years ago.
12.0 match 2.70 score
hesim-dev
hesim:Health Economic Simulation Modeling and Decision Analysis
A modular and computationally efficient R package for parameterizing, simulating, and analyzing health economic simulation models. The package supports cohort discrete time state transition models (Briggs et al. 1998) <doi:10.2165/00019053-199813040-00003>, N-state partitioned survival models (Glasziou et al. 1990) <doi:10.1002/sim.4780091106>, and individual-level continuous time state transition models (Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014>, encompassing both Markov (time-homogeneous and time-inhomogeneous) and semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is quantified with standard graphical and tabular summaries of a probabilistic sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) <doi:10.1002/hec.985>, <doi:10.1111/j.1524-4733.2008.00358.x>. Use of C++ and data.table make individual-patient simulation, probabilistic sensitivity analysis, and incorporation of patient heterogeneity fast.
Maintained by Devin Incerti. Last updated 6 months ago.
health-economic-evaluationmicrosimulationsimulation-modelingcpp
4.0 match 67 stars 8.12 score 41 scripts
pythonhealthdatascience
treat.sim:Nelson's Treatment Centre Simulation in Simmer
A discrete-event simulation of a simple urgent care treatment centre simulation from Nelson (2013). Implemented in R Simmer. The model is packaged to allow for easy experimentation, summary of results, and implementation in other software such as a Shiny interface.
Maintained by Thomas Monks. Last updated 8 months ago.
computer-simulationdiscrete-event-simulationhealthopen-modellingopen-scienceopen-sourcer-languagereproducible-researchsimmer
7.2 match 2 stars 4.48 score 5 scriptscran
entropy:Estimation of Entropy, Mutual Information and Related Quantities
Implements various estimators of entropy for discrete random variables, including the shrinkage estimator by Hausser and Strimmer (2009), the maximum likelihood and the Millow-Madow estimator, various Bayesian estimators, and the Chao-Shen estimator. It also offers an R interface to the NSB estimator. Furthermore, the package provides functions for estimating the Kullback-Leibler divergence, the chi-squared divergence, mutual information, and the chi-squared divergence of independence. It also computes the G statistic and the chi-squared statistic and corresponding p-values. Furthermore, there are functions for discretizing continuous random variables.
Maintained by Korbinian Strimmer. Last updated 3 years ago.
5.6 match 4 stars 5.68 score 62 dependents
rstudio
tfprobability:Interface to 'TensorFlow Probability'
Interface to 'TensorFlow Probability', a 'Python' library built on 'TensorFlow' that makes it easy to combine probabilistic models and deep learning on modern hardware ('TPU', 'GPU'). 'TensorFlow Probability' includes a wide selection of probability distributions and bijectors, probabilistic layers, variational inference, Markov chain Monte Carlo, and optimizers such as Nelder-Mead, BFGS, and SGLD.
Maintained by Tomasz Kalinowski. Last updated 3 years ago.
3.7 match 54 stars 8.63 score 221 scripts 3 dependents
mhahsler
markovDP:Infrastructure for Discrete-Time Markov Decision Processes (MDP)
Provides the infrastructure to work with Markov Decision Processes (MDPs) in R. The focus is on convenience in formulating MDPs, the support of sparse representations (using sparse matrices, lists and data.frames) and visualization of results. Some key components are implemented in C++ to speed up computation. Several popular solvers are implemented.
Maintained by Michael Hahsler. Last updated 3 days ago.
control-theorymarkov-decision-processoptimizationcpp
5.8 match 7 stars 5.51 score 4 scripts
comeetie
greed:Clustering and Model Selection with the Integrated Classification Likelihood
An ensemble of algorithms that enable the clustering of networks and data matrices (such as counts, categorical or continuous) with different type of generative models. Model selection and clustering is performed in combination by optimizing the Integrated Classification Likelihood (which is equivalent to minimizing the description length). Several models are available such as: Stochastic Block Model, degree corrected Stochastic Block Model, Mixtures of Multinomial, Latent Block Model. The optimization is performed thanks to a combination of greedy local search and a genetic algorithm (see <arXiv:2002:11577> for more details).
Maintained by Etienne Côme. Last updated 2 years ago.
5.3 match 14 stars 5.94 score 41 scripts
satijalab
Seurat:Tools for Single Cell Genomics
A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
Maintained by Paul Hoffman. Last updated 1 years ago.
human-cell-atlassingle-cell-genomicssingle-cell-rna-seqcpp
1.9 match 2.4k stars 16.86 score 50k scripts 73 dependents
julian-urbano
simIReff:Stochastic Simulation for Information Retrieval Evaluation: Effectiveness Scores
Provides tools for the stochastic simulation of effectiveness scores to mitigate data-related limitations of Information Retrieval evaluation research, as described in Urbano and Nagler (2018) <doi:10.1145/3209978.3210043>. These tools include: fitting, selection and plotting distributions to model system effectiveness, transformation towards a prespecified expected value, proxy to fitting of copula models based on these distributions, and simulation of new evaluation data from these distributions and copula models.
Maintained by Julián Urbano. Last updated 7 years ago.
10.4 match 3.00 score 20 scripts
statnet
ergm:Fit, Simulate and Diagnose Exponential-Family Models for Networks
An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis. See Hunter, Handcock, Butts, Goodreau, and Morris (2008) <doi:10.18637/jss.v024.i03> and Krivitsky, Hunter, Morris, and Klumb (2023) <doi:10.18637/jss.v105.i06>.
Maintained by Pavel N. Krivitsky. Last updated 7 days ago.
2.0 match 100 stars 15.36 score 1.4k scripts 36 dependents
csgillespie
poweRlaw:Analysis of Heavy Tailed Distributions
An implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.
Maintained by Colin Gillespie. Last updated 1 months ago.
2.4 match 112 stars 12.79 score 332 scripts 32 dependents
krahim
multitaper:Spectral Analysis Tools using the Multitaper Method
Implements multitaper spectral analysis using discrete prolate spheroidal sequences (Slepians) and sine tapers. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates. This package is an implementation of the method described in D.J. Thomson (1982) "Spectrum estimation and harmonic analysis" <doi:10.1109/PROC.1982.12433>.
Maintained by Karim Rahim. Last updated 8 months ago.
4.0 match 10 stars 7.62 score 67 scripts 26 dependents
meyerp-software
infotheo:Information-Theoretic Measures
Implements various measures of information theory based on several entropy estimators.
Maintained by Patrick E. Meyer. Last updated 3 years ago.
5.0 match 6.12 score 480 scripts 44 dependents
murrayefford
secr:Spatially Explicit Capture-Recapture
Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.
Maintained by Murray Efford. Last updated 2 days ago.
3.0 match 3 stars 10.18 score 410 scripts 5 dependents
radiant-rstats
radiant.basics:Basics Menu for Radiant: Business Analytics using R and Shiny
The Radiant Basics menu includes interfaces for probability calculation, central limit theorem simulation, comparing means and proportions, goodness-of-fit testing, cross-tabs, and correlation. The application extends the functionality in 'radiant.data'.
Maintained by Vincent Nijs. Last updated 10 months ago.
5.5 match 8 stars 5.56 score 79 scripts 3 dependents
best-practice-and-impact
afcharts:Produce Charts Following UK Government Analysis Function Guidance
Colour palettes and a 'ggplot2' theme to follow the UK Government Analysis Function best practice guidance for producing data visualisations, available at <https://analysisfunction.civilservice.gov.uk/policy-store/data-visualisation-charts/>. Includes continuous and discrete colour and fill scales, as well as a 'ggplot2' theme.
Maintained by Olivia Box Power. Last updated 2 months ago.
4.0 match 21 stars 7.61 score 7 scripts
wilkelab
ggridges:Ridgeline Plots in 'ggplot2'
Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.
Maintained by Claus O. Wilke. Last updated 3 months ago.
1.8 match 418 stars 16.71 score 14k scripts 285 dependents
rezamoammadi
BDgraph:Bayesian Structure Learning in Graphical Models using Birth-Death MCMC
Advanced statistical tools for Bayesian structure learning in undirected graphical models, accommodating continuous, ordinal, discrete, count, and mixed data. It integrates recent advancements in Bayesian graphical models as presented in the literature, including the works of Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi et al. (2021) <doi:10.1080/01621459.2021.1996377>, Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>, and Mohammadi et al. (2023) <doi:10.48550/arXiv.2307.00127>.
Maintained by Reza Mohammadi. Last updated 7 months ago.
4.0 match 8 stars 7.45 score 223 scripts 7 dependents
tnagler
vinereg:D-Vine Quantile Regression
Implements D-vine quantile regression models with parametric or nonparametric pair-copulas. See Kraus and Czado (2017) <doi:10.1016/j.csda.2016.12.009> and Schallhorn et al. (2017) <doi:10.48550/arXiv.1705.08310>.
Maintained by Thomas Nagler. Last updated 2 months ago.
copulaestimationstatisticsvinecpp
5.2 match 11 stars 5.76 score 26 scripts
epiverse-trace
epiparameter:Classes and Helper Functions for Working with Epidemiological Parameters
Classes and helper functions for loading, extracting, converting, manipulating, plotting and aggregating epidemiological parameters for infectious diseases. Epidemiological parameters extracted from the literature are loaded from the 'epiparameterDB' R package.
Maintained by Joshua W. Lambert. Last updated 2 months ago.
data-accessdata-packageepidemiologyepiverseprobability-distribution
3.0 match 33 stars 9.84 score 102 scripts 1 dependents
mdonoghoe
addreg:Additive Regression for Discrete Data
Methods for fitting identity-link GLMs and GAMs to discrete data, using EM-type algorithms with more stable convergence properties than standard methods.
Maintained by Mark W. Donoghoe. Last updated 7 years ago.
9.2 match 1 stars 3.20 score 16 scriptspredictiveecology
SpaDES:Develop and Run Spatially Explicit Discrete Event Simulation Models
Metapackage for implementing a variety of event-based models, with a focus on spatially explicit models. These include raster-based, event-based, and agent-based models. The core simulation components (provided by 'SpaDES.core') are built upon a discrete event simulation (DES; see Matloff (2011) ch 7.8.3 <https://nostarch.com/artofr.htm>) framework that facilitates modularity, and easily enables the user to include additional functionality by running user-built simulation modules (see also 'SpaDES.tools'). Included are numerous tools to visualize rasters and other maps (via 'quickPlot'), and caching methods for reproducible simulations (via 'reproducible'). Tools for running simulation experiments are provided by 'SpaDES.experiment'. Additional functionality is provided by the 'SpaDES.addins' and 'SpaDES.shiny' packages.
Maintained by Alex M Chubaty. Last updated 4 months ago.
simulation-frameworksimulation-toolkitspatially-explicit-models
3.3 match 55 stars 8.87 score 227 scripts
tomroh
fitur:Fit Univariate Distributions
Wrapper for computing parameters for univariate distributions using MLE. It creates an object that stores d, p, q, r functions as well as parameters and statistics for diagnostics. Currently supports automated fitting from base and actuar packages. A manually fitting distribution fitting function is included to support directly specifying parameters for any distribution from ancillary packages.
Maintained by Thomas Roh. Last updated 3 years ago.
5.5 match 4 stars 5.32 score 35 scripts
joemsong
GridOnClusters:Cluster-Preserving Multivariate Joint Grid Discretization
Discretize multivariate continuous data using a grid that captures the joint distribution via preserving clusters in the original data (Wang et al. 2020) <doi:10.1145/3388440.3412415>. Joint grid discretization is applicable as a data transformation step to prepare data for model-free inference of association, function, or causality.
Maintained by Joe Song. Last updated 10 months ago.
10.8 match 2.70 score 3 scripts
mikldk
disclap:Discrete Laplace Exponential Family
The discrete Laplace exponential family for use in fitting generalized linear models.
Maintained by Mikkel Meyer Andersen. Last updated 2 years ago.
9.2 match 3.18 score 3 scripts 1 dependents
juanmartinsantos
rgnoisefilt:Elimination of Noisy Samples in Regression Datasets using Noise Filters
Traditional noise filtering methods aim at removing noisy samples from a classification dataset. This package adapts classic and recent filtering techniques for use in regression problems, and it also incorporates methods specifically designed for regression data. In order to do this, it uses approaches proposed in the specialized literature, such as Martin et al. (2021) [<doi:10.1109/ACCESS.2021.3123151>] and Arnaiz-Gonzalez et al. (2016) [<doi:10.1016/j.eswa.2015.12.046>]. Thus, the goal of the implemented noise filters is to eliminate samples with noise in regression datasets.
Maintained by Juan Martin. Last updated 1 years ago.
7.3 match 2 stars 4.00 score 3 scripts
coleoguy
evobiR:Evolutionary Biology in R
Comparative analysis of continuous traits influencing discrete states, and utility tools to facilitate comparative analyses. Implementations of ABBA/BABA type statistics to test for introgression in genomic data.
Maintained by Heath Blackmon. Last updated 10 months ago.
4.0 match 15 stars 7.22 score 124 scripts
cvxgrp
CVXR:Disciplined Convex Optimization
An object-oriented modeling language for disciplined convex programming (DCP) as described in Fu, Narasimhan, and Boyd (2020, <doi:10.18637/jss.v094.i14>). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution. Interfaces to solvers on CRAN and elsewhere are provided, both commercial and open source.
Maintained by Anqi Fu. Last updated 4 months ago.
2.3 match 207 stars 12.89 score 768 scripts 51 dependentscran
biclust:BiCluster Algorithms
The main function biclust() provides several algorithms to find biclusters in two-dimensional data: Cheng and Church (2000, ISBN:1-57735-115-0), spectral (2003) <doi:10.1101/gr.648603>, plaid model (2005) <doi:10.1016/j.csda.2004.02.003>, xmotifs (2003) <doi:10.1142/9789812776303_0008> and bimax (2006) <doi:10.1093/bioinformatics/btl060>. In addition, the package provides methods for data preprocessing (normalization and discretisation), visualisation, and validation of bicluster solutions.
Maintained by Sebastian Kaiser. Last updated 2 years ago.
5.0 match 3 stars 5.79 score 160 scripts 16 dependents
ecortesgomez
DiscreteGapStatistic:An Extension of the Gap Statistic for Ordinal/Categorical Data
The gap statistic approach is extended to estimate the number of clusters for categorical response format data. This approach and accompanying software is designed to be used with the output of any clustering algorithm and with distances specifically designed for categorical (i.e. multiple choice) or ordinal survey response data.
Maintained by Eduardo Cortes. Last updated 11 days ago.
7.5 match 3.81 score 4 scripts
momx
Momocs:Morphometrics using R
The goal of 'Momocs' is to provide a complete, convenient, reproducible and open-source toolkit for 2D morphometrics. It includes most common 2D morphometrics approaches on outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. It allows reproducible, complex morphometrics analyses and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.
Maintained by Vincent Bonhomme. Last updated 1 years ago.
3.9 match 51 stars 7.42 score 346 scripts
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.
5.9 match 7 stars 4.89 score 22 scripts
priism-center
plotBart:Diagnostic and Plotting Functions to Supplement 'bartCause'
Functions to assist in diagnostics and plotting during the causal inference modeling process. Supplements the 'bartCause' package.
Maintained by Joseph Marlo. Last updated 10 months ago.
6.7 match 2 stars 4.30 score 20 scripts
olihawkins
tabbycat:Tabulate and Summarise Categorical Data
Functions for tabulating and summarising categorical variables. Most functions are designed to work with dataframes, and use the 'tidyverse' idiom of taking the dataframe as the first argument so they work within pipelines. Equivalent functions that operate directly on vectors are also provided where it makes sense. This package aims to make exploratory data analysis involving categorical variables quicker, simpler and more robust.
Maintained by Oliver Hawkins. Last updated 2 years ago.
6.7 match 36 stars 4.26 score 2 scriptsbioc
GmicR:Combines WGCNA and xCell readouts with bayesian network learrning to generate a Gene-Module Immune-Cell network (GMIC)
This package uses bayesian network learning to detect relationships between Gene Modules detected by WGCNA and immune cell signatures defined by xCell. It is a hypothesis generating tool.
Maintained by Richard Virgen-Slane. Last updated 5 months ago.
softwaresystemsbiologygraphandnetworknetworknetworkinferenceguiimmunooncologygeneexpressionqualitycontrolbayesianclustering
7.1 match 4.00 score 2 scripts
gbradburd
conStruct:Models Spatially Continuous and Discrete Population Genetic Structure
A method for modeling genetic data as a combination of discrete layers, within each of which relatedness may decay continuously with geographic distance. This package contains code for running analyses (which are implemented in the modeling language 'rstan') and visualizing and interpreting output. See the paper for more details on the model and its utility.
Maintained by Gideon Bradburd. Last updated 1 years ago.
3.4 match 35 stars 8.39 score 70 scripts
willgearty
deeptime:Plotting Tools for Anyone Working in Deep Time
Extends the functionality of other plotting packages (notably 'ggplot2') to help facilitate the plotting of data over long time intervals, including, but not limited to, geological, evolutionary, and ecological data. The primary goal of 'deeptime' is to enable users to add highly customizable timescales to their visualizations. Other functions are also included to assist with other areas of deep time visualization.
Maintained by William Gearty. Last updated 3 months ago.
geologyggplot2paleontologyvisualization
2.7 match 92 stars 10.61 score 207 scripts 3 dependents
matloff
regtools:Regression and Classification Tools
Tools for linear, nonlinear and nonparametric regression and classification. Novel graphical methods for assessment of parametric models using nonparametric methods. One vs. All and All vs. All multiclass classification, optional class probabilities adjustment. Nonparametric regression (k-NN) for general dimension, local-linear option. Nonlinear regression with Eickert-White method for dealing with heteroscedasticity. Utilities for converting time series to rectangular form. Utilities for conversion between factors and indicator variables. Some code related to "Statistical Regression and Classification: from Linear Models to Machine Learning", N. Matloff, 2017, CRC, ISBN 9781498710916.
Maintained by Norm Matloff. Last updated 2 months ago.
3.0 match 127 stars 9.39 score 48 scripts 3 dependents
khliland
fixedTimeEvents:The Distribution of Distances Between Discrete Events in Fixed Time
Distribution functions and test for over-representation of short distances in the Liland distribution. Simulation functions are included for comparison.
Maintained by Kristian Hovde Liland. Last updated 3 years ago.
7.5 match 3.74 score 11 scripts
r-forge
mpmi:Mixed-pair mutual information estimators
Uses a kernel smoothing approach to calculate Mutual Information for comparisons between all types of variables including continuous vs continuous, continuous vs discrete and discrete vs discrete. Uses a nonparametric bias correction giving Bias Corrected Mutual Information (BCMI). Implemented efficiently in Fortran 95 with OpenMP and suited to large genomic datasets.
Maintained by Chris Pardy. Last updated 11 years ago.
8.0 match 3.51 score 32 scripts
lukejharmon
geiger:Analysis of Evolutionary Diversification
Methods for fitting macroevolutionary models to phylogenetic trees Pennell (2014) <doi:10.1093/bioinformatics/btu181>.
Maintained by Luke Harmon. Last updated 2 years ago.
3.5 match 1 stars 7.84 score 2.3k scripts 28 dependentsbioc
hiReadsProcessor:Functions to process LM-PCR reads from 454/Illumina data
hiReadsProcessor contains set of functions which allow users to process LM-PCR products sequenced using any platform. Given an excel/txt file containing parameters for demultiplexing and sample metadata, the functions automate trimming of adaptors and identification of the genomic product. Genomic products are further processed for QC and abundance quantification.
Maintained by Nirav V Malani. Last updated 5 months ago.
6.6 match 4.18 score 7 scripts
ms609
TreeSearch:Phylogenetic Analysis with Discrete Character Data
Reconstruct phylogenetic trees from discrete data. Inapplicable character states are handled using the algorithm of Brazeau, Guillerme and Smith (2019) <doi:10.1093/sysbio/syy083> with the "Morphy" library, under equal or implied step weights. Contains a "shiny" user interface for interactive tree search and exploration of results, including character visualization, rogue taxon detection, tree space mapping, and cluster consensus trees (Smith 2022a, b) <doi:10.1093/sysbio/syab099>, <doi:10.1093/sysbio/syab100>. Profile Parsimony (Faith and Trueman, 2001) <doi:10.1080/10635150118627>, Successive Approximations (Farris, 1969) <doi:10.2307/2412182> and custom optimality criteria are implemented.
Maintained by Martin R. Smith. Last updated 3 days ago.
bioinformaticsmorphological-analysisphylogeneticsresearch-tooltree-searchcpp
3.5 match 7 stars 7.89 score 51 scripts