|
r-rri
|
public |
Testing and inference for regression models using residual randomization methods. The basis of inference is an invariance assumption on the regression errors, e.g., clustered errors, or doubly-clustered errors.
|
2025-03-25 |
|
r-rrf
|
public |
Feature Selection with Regularized Random Forest. This package is based on the 'randomForest' package by Andy Liaw. The key difference is the RRF() function that builds a regularized random forest. Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener, Regularized random forest for classification by Houtao Deng, Regularized random forest for regression by Xin Guan. Reference: Houtao Deng (2013) <arXiv:1306.0237>.
|
2025-03-25 |
|
r-rres
|
public |
Functions for studying realized genetic relatedness between people. Users will be able to simulate inheritance patterns given pedigree structures, generate SNP marker data given inheritance patterns, and estimate realized relatedness between pairs of individuals using SNP marker data. See Wang (2017) <doi:10.1534/genetics.116.197004>. This work was supported by National Institutes of Health grants R37 GM-046255.
|
2025-03-25 |
|
r-rrcov
|
public |
Robust Location and Scatter Estimation and Robust Multivariate Analysis with High Breakdown Point: principal component analysis (Filzmoser and Todorov (2013), <doi:10.1016/j.ins.2012.10.017>), linear and quadratic discriminant analysis (Todorov and Pires (2007)), multivariate tests (Todorov and Filzmoser (2010) <doi:10.1016/j.csda.2009.08.015>), outlier detection (Todorov et al. (2010) <doi:10.1007/s11634-010-0075-2>). See also Todorov and Filzmoser (2009) <urn:isbn:978-3838108148>, Todorov and Filzmoser (2010) <doi:10.18637/jss.v032.i03> and Boudt et al. (2019) <doi:10.1007/s11222-019-09869-x>.
|
2025-03-25 |
|
r-rrdrand
|
public |
Make use of the hardware random number accessed by the 'RdRand' instruction in recent Intel CPUs (Ivy Bridge and later). 'DRNG' is "Digital Random Number Generator".
|
2025-03-25 |
|
r-rptests
|
public |
Performs goodness of fits tests for both high and low-dimensional linear models. It can test for a variety of model misspecifications including nonlinearity and heteroscedasticity. In addition one can test the significance of potentially large groups of variables, and also produce p-values for the significance of individual variables in high-dimensional linear regression.
|
2025-03-25 |
|
r-rr
|
public |
Enables researchers to conduct multivariate statistical analyses of survey data with randomized response technique items from several designs, including mirrored question, forced question, and unrelated question. This includes regression with the randomized response as the outcome and logistic regression with the randomized response item as a predictor. In addition, tools for conducting power analysis for designing randomized response items are included. The package implements methods described in Blair, Imai, and Zhou (2015) ''Design and Analysis of the Randomized Response Technique,'' Journal of the American Statistical Association <https://graemeblair.com/papers/randresp.pdf>.
|
2025-03-25 |
|
r-rpostgres
|
public |
Fully DBI-compliant Rcpp-backed interface to PostgreSQL <https://www.postgresql.org/>, an open-source relational database.
|
2025-03-25 |
|
r-rpostgresql
|
public |
Database interface and 'PostgreSQL' driver for 'R'. This package provides a Database Interface 'DBI' compliant driver for 'R' to access 'PostgreSQL' database systems. In order to build and install this package from source, 'PostgreSQL' itself must be present your system to provide 'PostgreSQL' functionality via its libraries and header files. These files are provided as 'postgresql-devel' package under some Linux distributions. On 'macOS' and 'Microsoft Windows' system the attached 'libpq' library source will be used.
|
2025-03-25 |
|
r-rpresto
|
public |
Implements a 'DBI' compliant interface to Presto. Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes: <https://prestodb.io/>.
|
2025-03-25 |
|
r-rpicosat
|
public |
Bindings for the 'PicoSAT' solver to solve Boolean satisfiability problems (SAT). The boolean satisfiability problem asks the question if a given boolean formula can be TRUE; i.e. does there exist an assignment of TRUE/FALSE for each variable such that the whole formula is TRUE? The package bundles 'PicoSAT' solver release 965 <http://www.fmv.jku.at/picosat/>.
|
2025-03-25 |
|
r-rpms
|
public |
Functions to allow users to build and analyze design consistent tree and random forest models using survey data from a complex sample design. The tree model algorithm can fit a linear model to survey data in each node obtained by recursively partitioning the data. The splitting variables and selected splits are obtained using a randomized permutation test procedure which adjusted for complex sample design features used to obtain the data. Likewise the model fitting algorithm produces design-consistent coefficients to any specified least squares linear model between the dependent and independent variables used in the end nodes. The main functions return the resulting binary tree or random forest as an object of "rpms" or "rpms_forest" type. The package also provides methods modeling a "boosted" tree or forest model and a tree model for zero-inflated data as well as a number of functions and methods available for use with these object types.
|
2025-03-25 |
|
r-rpf
|
public |
Factor out logic and math common to Item Factor Analysis fitting, diagnostics, and analysis. It is envisioned as core support code suitable for more specialized IRT packages to build upon. Complete access to optimized C functions are made available with R_RegisterCCallable(). This software is described in Pritikin & Falk (2020) <doi:10.1177/0146621620929431>.
|
2025-03-25 |
|
r-rpact
|
public |
Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.
|
2025-03-25 |
|
r-roughsets
|
public |
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.
|
2025-03-25 |
|
r-roptim
|
public |
Perform general purpose optimization in R using C++. A unified wrapper interface is provided to call C functions of the five optimization algorithms ('Nelder-Mead', 'BFGS', 'CG', 'L-BFGS-B' and 'SANN') underlying optim().
|
2025-03-25 |
|
r-rotasym
|
public |
Implementation of the tests for rotational symmetry on the hypersphere proposed in García-Portugués, Paindaveine and Verdebout (2020) <doi:10.1080/01621459.2019.1665527>. The package also implements the proposed distributions on the hypersphere, based on the tangent-normal decomposition, and allows for the replication of the data application considered in the paper.
|
2025-03-25 |
|
r-ropj
|
public |
Read the data from Origin(R) project files ('*.opj') <https://www.originlab.com/doc/User-Guide/Origin-File-Types>. No write support is planned.
|
2025-03-25 |
|
r-rncl
|
public |
An interface to the Nexus Class Library which allows parsing of NEXUS, Newick and other phylogenetic tree file formats. It provides elements of the file that can be used to build phylogenetic objects such as ape's 'phylo' or phylobase's 'phylo4(d)'. This functionality is demonstrated with 'read_newick_phylo()' and 'read_nexus_phylo()'.
|
2025-03-25 |
|
r-rlemon
|
public |
Allows easy access to the LEMON Graph Library set of algorithms, written in C++. See the LEMON project page at <https://lemon.cs.elte.hu/trac/lemon>. Current LEMON version is 1.3.1.
|
2025-03-25 |
|
r-riskregression
|
public |
Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.
|
2025-03-25 |
|
r-rglpk
|
public |
R interface to the GNU Linear Programming Kit. 'GLPK' is open source software for solving large-scale linear programming (LP), mixed integer linear programming ('MILP') and other related problems.
|
2025-03-25 |
|
r-rgeolocate
|
public |
Connectors to online and offline sources for taking IP addresses and geolocating them to country, city, timezone and other geographic ranges. For individual connectors, see the package index.
|
2025-03-25 |
|
r-rfast2
|
public |
A collection of fast statistical and utility functions for data analysis. Functions for regression, maximum likelihood, column-wise statistics and many more have been included. C++ has been utilized to speed up the functions.
|
2025-03-25 |
|
r-rfast
|
public |
A collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions. References: a) Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>. b) Tsagris M. and Papadakis M. (2018). Forward regression in R: from the extreme slow to the extreme fast. Journal of Data Science, 16(4): 771--780. <doi:10.6339/JDS.201810_16(4).00006>.
|
2025-03-25 |
|
r-rcppziggurat
|
public |
The Ziggurat generator for normally distributed random numbers, originally proposed by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>) has been improved upon a few times starting with Leong et al (2005, <doi:10.18637/jss.v012.i07>). This package provides an aggregation in order to compare different implementations in order to provide an 'faster but good enough' alternative for use with R and C++ code.
|
2025-03-25 |
|
r-rbibutils
|
public |
Read and write 'Bibtex' files. Convert between bibliography formats, including 'Bibtex', 'Biblatex', 'PubMed', 'Endnote', and 'Bibentry'. Includes a port of the 'bibutils' utilities by Chris Putnam <https://sourceforge.net/projects/bibutils/>. Supports all bibliography formats and character encodings implemented in 'bibutils'.
|
2025-03-25 |
|
r-ragg
|
public |
Anti-Grain Geometry (AGG) is a high-quality and high-performance 2D drawing library. The 'ragg' package provides a set of graphic devices based on AGG to use as alternative to the raster devices provided through the 'grDevices' package.
|
2025-03-25 |
|
r-proj
|
public |
Currently non-operational, a harmless wrapper to allow package 'reproj' to install and function while relying on the 'proj4' package.
|
2025-03-25 |
|
r-pomdpsolve
|
public |
Installs an updated version of 'pomdp-solve', a program to solve Partially Observable Markov Decision Processes (POMDPs) using a variety of exact and approximate value iteration algorithms. A convenient R infrastructure is provided in the separate package pomdp. Kaelbling, Littman and Cassandra (1998) <doi:10.1016/S0004-3702(98)00023-X>.
|
2025-03-25 |
|
r-pkgcache
|
public |
Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.
|
2025-03-25 |
|
r-phangorn
|
public |
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).
|
2025-03-25 |
|
r-pec
|
public |
Validation of risk predictions obtained from survival models and competing risk models based on censored data using inverse weighting and cross-validation. Most of the 'pec' functionality has been moved to 'riskRegression'.
|
2025-03-25 |
|
r-msm
|
public |
Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal data. Designed for processes observed at arbitrary times in continuous time (panel data) but some other observation schemes are supported. Both Markov transition rates and the hidden Markov output process can be modelled in terms of covariates, which may be constant or piecewise-constant in time.
|
2025-03-25 |
|
r-morpho
|
public |
A toolset for Geometric Morphometrics and mesh processing. This includes (among other stuff) mesh deformations based on reference points, permutation tests, detection of outliers, processing of sliding semi-landmarks and semi-automated surface landmark placement.
|
2025-03-25 |
|
r-mets
|
public |
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>. Also contains two-stage binomial modelling that can do pairwise odds-ratio dependence modelling based marginal logistic regression models. This is an alternative to the alternating logistic regression approach (ALR).
|
2025-03-25 |
|
r-meanshiftr
|
public |
Performs mean shift classification using linear and k-d tree based nearest neighbor implementations for the Gaussian, Epanechnikov, and biweight product kernels.
|
2025-03-25 |
|
r-meanr
|
public |
Sentiment analysis is a popular technique in text mining that attempts to determine the emotional state of some text. We provide a new implementation of a common method for computing sentiment, whereby words are scored as positive or negative according to a dictionary lookup. Then the sum of those scores is returned for the document. We use the 'Hu' and 'Liu' sentiment dictionary ('Hu' and 'Liu', 2004) <doi:10.1145/1014052.1014073> for determining sentiment. The scoring function is 'vectorized' by document, and scores for multiple documents are computed in parallel via 'OpenMP'.
|
2025-03-25 |
|
r-mdfs
|
public |
Functions for MultiDimensional Feature Selection (MDFS): calculating multidimensional information gains, scoring variables, finding important variables, plotting selection results. This package includes an optional CUDA implementation that speeds up information gain calculation using NVIDIA GPGPUs. R. Piliszek et al. (2019) <doi:10.32614/RJ-2019-019>.
|
2025-03-25 |
|
r-mda
|
public |
Mixture and flexible discriminant analysis, multivariate adaptive regression splines (MARS), BRUTO, and vector-response smoothing splines. Hastie, Tibshirani and Friedman (2009) "Elements of Statistical Learning (second edition, chap 12)" Springer, New York.
|
2025-03-25 |
|
r-mcr
|
public |
Regression methods to quantify the relation between two measurement methods are provided by this package. In particular it addresses regression problems with errors in both variables and without repeated measurements. It implements the CLSI recommendations (see J. A. Budd et al. (2018, <https://clsi.org/standards/products/method-evaluation/documents/ep09/>) for analytical method comparison and bias estimation using patient samples. Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators are implemented, see F. Dufey (2020, <doi:10.1515/ijb-2019-0157>) and J. Raymaekers and F. Dufey (2022, <arXiv:2202:08060>). A comprehensive overview over the implemented methods and references can be found in the manual pages "mcr-package" and "mcreg".
|
2025-03-25 |
|
r-mco
|
public |
A collection of function to solve multiple criteria optimization problems using genetic algorithms (NSGA-II). Also included is a collection of test functions.
|
2025-03-25 |
|
r-mcmcprecision
|
public |
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.
|
2025-03-25 |
|
r-mcmcse
|
public |
Provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE computation for expectation and quantile estimators is supported as well as multivariate estimations. The package also provides functions for computing effective sample size and for plotting Monte Carlo estimates versus sample size.
|
2025-03-25 |
|
r-mcmcpack
|
public |
Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return 'coda' mcmc objects that can then be summarized using the 'coda' package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
|
2025-03-25 |
|
r-mcmc
|
public |
Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, <doi:10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.
|
2025-03-25 |
|
r-mcglm
|
public |
Fitting multivariate covariance generalized linear models (McGLMs) to data. McGLM is a general framework for non-normal multivariate data analysis, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. The models take non-normality into account in the conventional way by means of a variance function, and the mean structure is modelled by means of a link function and a linear predictor. The models are fitted using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of different types of response variables and covariance structures, including multivariate extensions of repeated measures, time series, longitudinal, spatial and spatio-temporal structures. The package offers a user-friendly interface for fitting McGLMs similar to the glm() R function. See Bonat (2018) <doi:10.18637/jss.v084.i04>, for more information and examples.
|
2025-03-25 |
|
r-mclust
|
public |
Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.
|
2025-03-25 |
|
r-mcclust
|
public |
Implements methods for processing a sample of (hard) clusterings, e.g. the MCMC output of a Bayesian clustering model. Among them are methods that find a single best clustering to represent the sample, which are based on the posterior similarity matrix or a relabelling algorithm.
|
2025-03-25 |
|
r-mba
|
public |
Functions to interpolate irregularly and regularly spaced data using Multilevel B-spline Approximation (MBA). Functions call portions of the SINTEF Multilevel B-spline Library written by Øyvind Hjelle which implements methods developed by Lee, Wolberg and Shin (1997; <doi:10.1109/2945.620490>).
|
2025-03-25 |
