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r-rip46
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public |
Utility functions and S3 classes for IPv4 and IPv6 addresses, including conversion to and from binary representation.
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2025-03-25 |
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r-rinsp
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Functions to calculate several ecological indices of individual and population niche width (Araujo's E, clustering and pairwise similarity among individuals, IS, Petraitis' W, and Roughgarden's WIC/TNW) to assess individual specialization based on data of resource use. Resource use can be quantified by counts of categories, measures of mass/lenght or proportions. Monte Carlo resampling procedures are available for hypothesis testing against multinomial null models.
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2025-03-25 |
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r-rinside
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public |
C++ classes to embed R in C++ applications A C++ class providing the R interpreter is offered by this package making it easier to have "R inside" your C++ application. As R itself is embedded into your application, a shared library build of R is required. This works on Linux, OS X and even on Windows provided you use the same tools used to build R itself. d Numerous examples are provided in the eight subdirectories of the examples/ directory of the installed package: standard, 'mpi' (for parallel computing), 'qt' (showing how to embed 'RInside' inside a Qt GUI application), 'wt' (showing how to build a "web-application" using the Wt toolkit), 'armadillo' (for 'RInside' use with 'RcppArmadillo') and 'eigen' (for 'RInside' use with 'RcppEigen'). The examples use 'GNUmakefile(s)' with GNU extensions, so a GNU make is required (and will use the 'GNUmakefile' automatically). 'Doxygen'-generated documentation of the C++ classes is available at the 'RInside' website as well.
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2025-03-25 |
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r-ring
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public |
Circular / ring buffers in R and C. There are a couple of different buffers here with different implementations that represent different trade-offs.
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2025-03-25 |
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r-ridge
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public |
Linear and logistic ridge regression functions. Additionally includes special functions for genome-wide single-nucleotide polymorphism (SNP) data.
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2025-03-25 |
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r-ri2by2
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public |
Computes attributable effects based confidence interval, permutation test confidence interval, or asymptotic confidence interval for the the average treatment effect on a binary outcome.
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2025-03-25 |
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r-rhpcblasctl
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public |
Control the number of threads on 'BLAS' (Aka 'GotoBLAS', 'OpenBLAS', 'ACML', 'BLIS' and 'MKL'). And possible to control the number of threads in 'OpenMP'. Get a number of logical cores and physical cores if feasible.
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2025-03-25 |
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r-rhli
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public |
Complete access from 'R' to the FIS 'MarketMap C-Toolkit' ('FAME C-HLI'). 'FAME' is a fully integrated software and database management system from FIS that provides the following capabilities: Time series and cross-sectional data management; Financial calculation, data analysis, econometrics, and forecasting; Table generation and detailed multicolor, presentation-quality report writing; Multicolor, presentation-quality graphics; "What-if" analysis; Application development and structured programming; Data transfer to and from other applications; Tools for building customized graphical user interfaces.
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2025-03-25 |
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r-rgeos
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Interface to Geometry Engine - Open Source ('GEOS') using the C 'API' for topology operations on geometries. The 'GEOS' library is external to the package, and, when installing the package from source, must be correctly installed first. Windows and Mac Intel OS X binaries are provided on 'CRAN'. ('rgeos' >= 0.5-1): Up to and including 'GEOS' 3.7.1, topological operations succeeded with some invalid geometries for which the same operations fail from and including 'GEOS' 3.7.2. The 'checkValidity=' argument defaults and structure have been changed, from default FALSE to integer default '0L' for 'GEOS' < 3.7.2 (no check), '1L' 'GEOS' >= 3.7.2 (check and warn). A value of '2L' is also provided that may be used, assigned globally using 'set_RGEOS_CheckValidity(2L)', or locally using the 'checkValidity=2L' argument, to attempt zero-width buffer repair if invalid geometries are found. The previous default (FALSE, now '0L') is fastest and used for 'GEOS' < 3.7.2, but will not warn users of possible problems before the failure of topological operations that previously succeeded.
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2025-03-25 |
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r-rgeode
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Provides the hybrid Bayesian method Geometric Density Estimation. On the one hand, it scales the dimension of our data, on the other it performs inference. The method is fully described in the paper "Scalable Geometric Density Estimation" by Y. Wang, A. Canale, D. Dunson (2016) <http://proceedings.mlr.press/v51/wang16e.pdf>.
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2025-03-25 |
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r-rgenoud
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public |
A genetic algorithm plus derivative optimizer.
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2025-03-25 |
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r-rgbm
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Provides an implementation of Regularized LS-TreeBoost & LAD-TreeBoost algorithm for Regulatory Network inference from any type of expression data (Microarray/RNA-seq etc). See Mall et al (2017) <doi:10.1101/132670>.
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2025-03-25 |
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r-rgb
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Classes and methods to efficiently handle (slice, annotate, draw ...) genomic features (such as genes or transcripts), and an interactive interface to browse them.
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2025-03-25 |
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r-rforensicbatwing
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A modified version (with great help from Ian J. Wilson) of Ian J. Wilson's program BATWING for calculating forensic trace-suspect match probabilities.
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2025-03-25 |
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r-rfit
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public |
R estimation and inference for linear models. Estimation is for general scores and a library of commonly used score functions is included.
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2025-03-25 |
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r-rferns
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public |
Provides the random ferns classifier by Ozuysal, Calonder, Lepetit and Fua (2009) <doi:10.1109/TPAMI.2009.23>, modified for generic and multi-label classification and featuring OOB error approximation and importance measure as introduced in Kursa (2014) <doi:10.18637/jss.v061.i10>.
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2025-03-25 |
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r-rexpokit
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public |
Wraps some of the matrix exponentiation utilities from EXPOKIT (<http://www.maths.uq.edu.au/expokit/>), a FORTRAN library that is widely recommended for matrix exponentiation (Sidje RB, 1998. "Expokit: A Software Package for Computing Matrix Exponentials." ACM Trans. Math. Softw. 24(1): 130-156). EXPOKIT includes functions for exponentiating both small, dense matrices, and large, sparse matrices (in sparse matrices, most of the cells have value 0). Rapid matrix exponentiation is useful in phylogenetics when we have a large number of states (as we do when we are inferring the history of transitions between the possible geographic ranges of a species), but is probably useful in other ways as well.
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2025-03-25 |
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r-rexperigen
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Provides convenience functions to communicate with an Experigen server: Experigen (<http://github.com/aquincum/experigen>) is an online framework for creating linguistic experiments, and it stores the results on a dedicated server. This package can be used to retrieve the results from the server, and it is especially helpful with registered experiments, as authentication with the server has to happen.
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2025-03-25 |
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r-retimes
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Reaction time analysis by maximum likelihood
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2025-03-25 |
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r-restrictedmvn
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A fast Gibbs sampler for multivariate normal with affine constraints.
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2025-03-25 |
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r-resemble
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public |
Implementation of functions for spectral similarity/dissimilarity analysis and memory-based learning (MBL) for non-linear modeling in complex spectral datasets. In chemometrics MBL is also known as local modeling.
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2025-03-25 |
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r-repolr
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public |
Fits linear models to repeated ordinal scores using GEE methodology.
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2025-03-25 |
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r-repfdr
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public |
Estimation of Bayes and local Bayes false discovery rates for replicability analysis (Heller & Yekutieli, 2014 <doi:10.1214/13-AOAS697> ; Heller at al., 2015 <doi: 10.1093/bioinformatics/btu434>).
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2025-03-25 |
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r-reordercluster
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public |
Tools for performing the leaf reordering for the dendrogram that preserves the hierarchical clustering result and at the same time tries to group instances from the same class together.
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2025-03-25 |
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r-remmap
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remMap is developed for fitting multivariate response regression models under the high-dimension-low-sample-size setting
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2025-03-25 |
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r-rem
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Calculate endogenous network effects in event sequences and fit relational event models (REM): Using network event sequences (where each tie between a sender and a target in a network is time-stamped), REMs can measure how networks form and evolve over time. Endogenous patterns such as popularity effects, inertia, similarities, cycles or triads can be calculated and analyzed over time.
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2025-03-25 |
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r-relsurv
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Contains functions for analysing relative survival data, including nonparametric estimators of net (marginal relative) survival, relative survival ratio, crude mortality, methods for fitting and checking additive and multiplicative regression models, transformation approach, methods for dealing with population mortality tables.
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2025-03-25 |
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r-relatedness
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Inference of relatedness coefficients from a bi-allelic genotype matrix using a Maximum Likelihood estimation, Laporte, F., Charcosset, A. and Mary-Huard, T. (2017) <doi:10.1111/biom.12634>.
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2025-03-25 |
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r-reins
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Functions from the book "Reinsurance: Actuarial and Statistical Aspects" (2017) by Hansjoerg Albrecher, Jan Beirlant and Jef Teugels <http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470772689.html>.
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2025-03-25 |
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r-regnet
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Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations among genomic features. This package provides procedures of network-based variable selection for generalized linear models (Ren et al. (2017) <doi:10.1186/s12863-017-0495-5> and Ren et al. (2019) <doi:10.1002/gepi.22194>). Two recent additions are the robust network regularization for the survival response and the network regularization for continuous response. Functions for other regularization methods will be included in the forthcoming upgraded versions.
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2025-03-25 |
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r-reglogit
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Regularized (polychotomous) logistic regression by Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified interface.
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2025-03-25 |
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r-refinr
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These functions take a character vector as input, identify and cluster similar values, and then merge clusters together so their values become identical. The functions are an implementation of the key collision and ngram fingerprint algorithms from the open source tool Open Refine <http://openrefine.org/>. More info on key collision and ngram fingerprint can be found here <https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth>.
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2025-03-25 |
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r-redm
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A new implementation of EDM algorithms based on research software previously developed for internal use in the Sugihara Lab (UCSD/SIO). Contains C++ compiled objects that use time delay embedding to perform state-space reconstruction and nonlinear forecasting and an R interface to those objects using 'Rcpp'. It supports both the simplex projection method from Sugihara & May (1990) <DOI:10.1038/344734a0> and the S-map algorithm in Sugihara (1994) <DOI:10.1098/rsta.1994.0106>. In addition, this package implements convergent cross mapping as described in Sugihara et al. (2012) <DOI:10.1126/science.1227079> and multiview embedding as described in Ye & Sugihara (2016) <DOI:10.1126/science.aag0863>.
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2025-03-25 |
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r-recurse
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public |
Computes revisitation metrics for trajectory data, such as the number of revisitations for each location as well as the time spent for that visit and the time since the previous visit. Also includes functions to plot data.
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2025-03-25 |
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r-recosystem
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R wrapper of the 'libmf' library <http://www.csie.ntu.edu.tw/~cjlin/libmf/> for recommender system using matrix factorization. It is typically used to approximate an incomplete matrix using the product of two matrices in a latent space. Other common names for this task include "collaborative filtering", "matrix completion", "matrix recovery", etc. High performance multi-core parallel computing is supported in this package.
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2025-03-25 |
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r-reconstructr
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public |
Functions to reconstruct sessions from web log or other user trace data and calculate various metrics around them, producing tabular, output that is compatible with 'dplyr' or 'data.table' centered processes.
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2025-03-25 |
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r-rebmix
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public |
R functions for random univariate and multivariate finite mixture model generation, estimation, clustering, latent class analysis and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, binomial, Poisson, Dirac or circular von Mises parametric families.
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2025-03-25 |
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r-realvams
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Fits a multivariate value-added model (VAM), see Broatch, Green, and Karl (2018) <doi:10.32614/RJ-2018-033> and Broatch and Lohr (2012) <doi:10.3102/1076998610396900>, with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) <doi:10.1080/00949659308811554>, is used for the estimation of this joint generalized linear mixed model. The inner loop of the pseudo-likelihood routine (estimation of a linear mixed model) occurs in the framework of the EM algorithm presented by Karl, Yang, and Lohr (2013) <DOI:10.1016/j.csda.2012.10.004>. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.
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2025-03-25 |
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r-gifski
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Multi-threaded GIF encoder written in Rust: <https://gif.ski/>. Converts images to GIF animations using pngquant's efficient cross-frame palettes and temporal dithering with thousands of colors per frame.
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2025-03-25 |
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r-glmpath
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A path-following algorithm for L1 regularized generalized linear models and Cox proportional hazards model.
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2025-03-25 |
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r-glmmsr
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Conduct inference about generalized linear mixed models, with a choice about which method to use to approximate the likelihood. In addition to the Laplace and adaptive Gaussian quadrature approximations, which are borrowed from 'lme4', the likelihood may be approximated by the sequential reduction approximation, or an importance sampling approximation. These methods provide an accurate approximation to the likelihood in some situations where it is not possible to use adaptive Gaussian quadrature.
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2025-03-25 |
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r-glmmml
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public |
Binomial and Poisson regression for clustered data, fixed and random effects with bootstrapping.
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2025-03-25 |
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r-glmlep
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Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by LEP.
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2025-03-25 |
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r-glmgraph
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We propose to use sparse regression model to achieve variable selection while accounting for graph-constraints among coefficients. Different linear combination of a sparsity penalty(L1) and a smoothness(MCP) penalty has been used, which induces both sparsity of the solution and certain smoothness on the linear coefficients.
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2025-03-25 |
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r-glm.deploy
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Provides two functions that generate source code implementing the predict function of fitted glm objects. In this version, code can be generated for either 'C' or 'Java'. The idea is to provide a tool for the easy and fast deployment of glm predictive models into production. The source code generated by this package implements two function/methods. One of such functions implements the equivalent to predict(type="response"), while the second implements predict(type="link"). Source code is written to disk as a .c or .java file in the specified path. In the case of c, an .h file is also generated.
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2025-03-25 |
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r-glmaspu
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Several tests for high dimensional generalized linear models have been proposed recently. In this package, we implemented a new test called adaptive sum of powered score (aSPU) for high dimensional generalized linear models, which is often more powerful than the existing methods in a wide scenarios. We also implemented permutation based version of several existing methods for research purpose. We recommend users use the aSPU test for their real testing problem. You can learn more about the tests implemented in the package via the following papers: 1. Pan, W., Kim, J., Zhang, Y., Shen, X. and Wei, P. (2014) <DOI:10.1534/genetics.114.165035> A powerful and adaptive association test for rare variants, Genetics, 197(4). 2. Guo, B., and Chen, S. X. (2016) <DOI:10.1111/rssb.12152>. Tests for high dimensional generalized linear models. Journal of the Royal Statistical Society: Series B. 3. Goeman, J. J., Van Houwelingen, H. C., and Finos, L. (2011) <DOI:10.1093/biomet/asr016>. Testing against a high-dimensional alternative in the generalized linear model: asymptotic type I error control. Biometrika, 98(2).
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2025-03-25 |
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r-gllm
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Routines for log-linear models of incomplete contingency tables, including some latent class models, via EM and Fisher scoring approaches. Allows bootstrapping. See Espeland and Hui (1987) <doi:10.2307/2531553> for general approach.
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2025-03-25 |
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r-glinternet
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Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical group-lasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015) <DOI:10.1080/10618600.2014.938812>.
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2025-03-25 |
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r-glide
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Functions evaluate global and individual tests for direct effects in Mendelian randomization studies.
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2025-03-25 |
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r-gldex
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The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution.
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2025-03-25 |
