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r-treeman
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public |
S4 class and methods for intuitive and efficient phylogenetic tree manipulation.
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2023-06-16 |
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r-tmg
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public |
Random number generation of truncated multivariate Gaussian distributions using Hamiltonian Monte Carlo. The truncation is defined using linear and/or quadratic polynomials.
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2023-06-16 |
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r-tsc
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Performs the two-sample comparisons using the following exact test procedures: the exact likelihood-ratio test (LRT) for equality of two normal populations proposed in Zhang et al. (2012); the combined test based on the LRT and Shapiro-Wilk test for normality via the Bonferroni correction technique; the newly proposed density-based empirical likelihood (DBEL) ratio test. To calculate p-values of the DBEL procedures, three procedures are used: (a) the traditional Monte Carlo (MC) method implemented in C++, (b) a new interpolation method based on regression techniques to operate with tabulated critical values of the test statistic; (c) a Bayesian type method that uses the tabulated critical values as the prior information and MC generated DBEL-test-statistic's values as data.
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2023-06-16 |
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r-vbsr
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Efficient algorithm for solving ultra-sparse regularized regression models using a variational Bayes algorithm with a spike (l0) prior. Algorithm is solved on a path, with coordinate updates, and is capable of generating very sparse models. There are very general model diagnostics for controling type-1 error included in this package.
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2023-06-16 |
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r-treeperm
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An implementation of permutation tests in R, supporting both exact and asymptotic K sample test of data locations. The p value of exact tests is found using tree algorithms. Tree algorithms treat permutations of input data as tree nodes and perform constraint depth-first searches for permutations that fall into the critical region of a test systematically. Pruning of tree search and optimisations at C level enable exact tests for certain large data sets.
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2023-06-16 |
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r-vnm
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Provide tools for finding multiple-objective optimal designs for estimating the shape of dose-response, the ED50 (the dose producing an effect midway between the expected responses at the extreme doses) and the MED (the minimum effective dose level) for the 2,3,4-parameter logistic models and for evaluating its efficiencies for the three objectives. The acronym VNM stands for V-algorithm using Newton Raphson method to search multiple-objective optimal design.
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2023-06-16 |
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r-validatejsonr
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The current implementation uses the C++ library 'RapidJSON' to supply the schema functionality, it supports JSON Schema Draft v4. As of 2016-09-09, 'RapidJSON' passed 262 out of 263 tests in JSON Schema Test Suite (JSON Schema draft 4).
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2023-06-16 |
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r-waffect
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waffect (pronounced 'double-u affect' for 'weighted affectation') is a package to simulate phenotypic (case or control) datasets under a disease model H1 such that the total number of cases is constant across all the simulations (the constrain in the title). The package also makes it possible to generate phenotypes in the case of more than two classes, so that the number of phenotypes belonging to each class is constant across all the simulations. waffect is used to assess empirically the statistical power of Genome Wide Association studies.
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2023-06-16 |
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r-robfitcongraph
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Contains a single function named robFitConGraph() which includes two algorithms for robust estimation of scatter matrices subject to zero-constraints in its inverse. The methodology is described in Vogel & Tyler (2014) <doi:10.1093/biomet/asu041>. See robFitConGraph() function documentation for further details.
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2023-06-16 |
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r-rip46
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Utility functions and S3 classes for IPv4 and IPv6 addresses, including conversion to and from binary representation.
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2023-06-16 |
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r-ri2by2
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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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2023-06-16 |
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r-rhli
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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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2023-06-16 |
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r-restrictedmvn
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A fast Gibbs sampler for multivariate normal with affine constraints.
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2023-06-16 |
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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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2023-06-16 |
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r-rexpokit
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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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2023-06-16 |
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r-robustgam
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This package provides robust estimation for generalized additive models. It implements a fast and stable algorithm in Wong, Yao and Lee (2013). The implementation also contains three automatic selection methods for smoothing parameter. They are designed to be robust to outliers. For more details, see Wong, Yao and Lee (2013).
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2023-06-16 |
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r-rmumps
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Some basic features of MUMPS (Multifrontal Massively Parallel sparse direct Solver) are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: PORD, METIS, SCOTCH. MUMPS method was first described in Amestoy et al. (2001) <doi:10.1137/S0895479899358194> and Amestoy et al. (2006) <doi:10.1016/j.parco.2005.07.004>.
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2023-06-16 |
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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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2023-06-16 |
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r-rlda
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Estimates the Bayesian LDA model for mixed-membership clustering based on different types of data (i.e., Multinomial, Bernoulli, and Binomial entries). Albuquerque, Valle and Li (2019) <doi:10.1016/j.knosys.2018.10.024>.
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2023-06-16 |
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r-rollregres
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Methods for fast rolling and expanding linear regression models. That is, series of linear regression models estimated on either an expanding window of data or a moving window of data. The methods use rank-one updates and downdates of the upper triangular matrix from a QR decomposition (see Dongarra, Moler, Bunch, and Stewart (1979) <doi:10.1137/1.9781611971811>).
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2023-06-16 |
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r-rjacgh
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Bayesian analysis of CGH microarrays fitting Hidden Markov Chain models. The selection of the number of states is made via their posterior probability computed by Reversible Jump Markov Chain Monte Carlo Methods. Also returns probabilistic common regions for gains/losses.
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2023-06-16 |
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r-reordercluster
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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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2023-06-16 |
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r-retimes
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Reaction time analysis by maximum likelihood
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2023-06-16 |
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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. Please note that 'rgeos' will be retired by the end of 2023, plan transition to sf functions using 'GEOS' at your earliest convenience. 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. From 'GEOS' 3.8.0, repair of geometries may also be attempted using 'gMakeValid()', which may, however, return a collection of geometries of different types.
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2023-06-16 |
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r-rgdal
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Provides bindings to the 'Geospatial' Data Abstraction Library ('GDAL') (>= 1.11.4) and access to projection/transformation operations from the 'PROJ' library. Please note that 'rgdal' will be retired by the end of 2023, plan transition to sf/stars/'terra' functions using 'GDAL' and 'PROJ' at your earliest convenience. Use is made of classes defined in the 'sp' package. Raster and vector map data can be imported into R, and raster and vector 'sp' objects exported. The 'GDAL' and 'PROJ' libraries are external to the package, and, when installing the package from source, must be correctly installed first; it is important that 'GDAL' < 3 be matched with 'PROJ' < 6. From 'rgdal' 1.5-8, installed with to 'GDAL' >=3, 'PROJ' >=6 and 'sp' >= 1.4, coordinate reference systems use 'WKT2_2019' strings, not 'PROJ' strings. 'Windows' and 'macOS' binaries (including 'GDAL', 'PROJ' and their dependencies) are provided on 'CRAN'.
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2023-06-16 |
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r-rknn
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Random knn classification and regression are implemented. Random knn based feature selection methods are also included. The approaches are mainly developed for high-dimensional data with small sample size.
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2023-06-16 |
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r-rmecabko
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An 'Rcpp' interface for Eunjeon project <http://eunjeon.blogspot.com/>. The 'mecab-ko' and 'mecab-ko-dic' is based on a C++ library, and part-of-speech tagging with them is useful when the spacing of source Korean text is not correct. This package provides part-of-speech tagging and tokenization function for Korean text.
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2023-06-16 |
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r-rodbcext
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An extension for RODBC package adding support for parameterized queries.
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2023-06-16 |
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r-rngwell19937
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Long period linear random number generator WELL19937a by F. Panneton, P. L'Ecuyer and M. Matsumoto. The initialization algorithm allows to seed the generator with a numeric vector of an arbitrary length and uses MRG32k5a by P. L'Ecuyer to achieve good quality of the initialization. The output function may be set to provide numbers from the interval (0,1) with 53 (the default) or 32 random bits. WELL19937a is of similar type as Mersenne Twister and has the same period. WELL19937a is slightly slower than Mersenne Twister, but has better equidistribution and "bit-mixing" properties and faster recovery from states with prevailing zeros than Mersenne Twister. All WELL generators with orders 512, 1024, 19937 and 44497 can be found in randtoolbox package.
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2023-06-16 |
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r-rlm
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Robust fitting of linear model which can take response in matrix form.
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2023-06-16 |
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r-fmrs
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Provides parameter estimation as well as variable selection in Finite Mixture of Accelerated Failure Time Regression and Finite Mixture of Regression Models. Furthermore, this package provides Ridge Regression and Elastic Net.
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2023-06-16 |
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r-soda
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Functions, examples and other software related to the book "Software for Data Analysis: Programming with R". See package?SoDA for an overview.
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2023-06-16 |
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r-snipem
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Snipping methods optimally removing scattered cells for robust estimation and cluster analysis.
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2023-06-16 |
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r-smisc
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A collection of functions for statistical computing and data manipulation in R. Includes routines for data ingestion, operating on dataframes and matrices, conversion to and from lists, converting factors, filename manipulation, programming utilities, parallelization, plotting, statistical and mathematical operations, and time series.
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2023-06-16 |
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r-sequences
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Educational package used in R courses to illustrate object-oriented programming and package development. Using biological sequences (DNA and RNA) as a working example.
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2023-06-16 |
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r-spatimeclus
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Mixture model is used to achieve the clustering goal. Each component is itself a mixture model of polynomial autoregressive regressions whose the logistic weights consider the spatial and temporal information.
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2023-06-16 |
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r-pwd
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Contains functions which allow the user to perform time series regression quickly using the Power Weighted Densities (PWD) approach. alphahat_LR_one_Rcpp() is the main workhorse function within this package.
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2023-06-16 |
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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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2023-06-16 |
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r-gforce
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A complete suite of computationally efficient methods for high dimensional clustering and inference problems in G-Latent Models (a type of Latent Variable Gaussian graphical model). The main feature is the FORCE (First-Order, Certifiable, Efficient) clustering algorithm which is a fast solver for a semi-definite programming (SDP) relaxation of the K-means problem. For certain types of graphical models (G-Latent Models), with high probability the algorithm not only finds the optimal clustering, but produces a certificate of having done so. This certificate, however, is model independent and so can also be used to certify data clustering problems. The 'GFORCE' package also contains implementations of inferential procedures for G-Latent graphical models using n-fold cross validation. Also included are native code implementations of other popular clustering methods such as Lloyd's algorithm with kmeans++ initialization and complete linkage hierarchical clustering. The FORCE method is due to Eisenach and Liu (2019) <arxiv:1806.00530>.
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2023-06-16 |
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r-smc
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particle filtering, auxiliary particle filtering and sequential Monte Carlo algorithms
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2023-06-16 |
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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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2023-06-16 |
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r-sdmtools
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This packages provides a set of tools for post processing the outcomes of species distribution modeling exercises. It includes novel methods for comparing models and tracking changes in distributions through time. It further includes methods for visualizing outcomes, selecting thresholds, calculating measures of accuracy and landscape fragmentation statistics, etc.. This package was made possible in part by financial support from the Australian Research Council & ARC Research Network for Earth System Science.
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2023-06-16 |
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r-skda
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Sparse (Multicategory) Kernel Discriminant Analysis does variable selection for nonparametric classification
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2023-06-16 |
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r-ftnonpar
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The package contains R-functions to perform the methods in nonparametric regression and density estimation, described in Davies, P. L. and Kovac, A. (2001) Local Extremes, Runs, Strings and Multiresolution (with discussion) Annals of Statistics. 29. p1-65 Davies, P. L. and Kovac, A. (2004) Densities, Spectral Densities and Modality Annals of Statistics. Annals of Statistics. 32. p1093-1136 Kovac, A. (2006) Smooth functions and local extreme values. Computational Statistics and Data Analysis (to appear) D\"umbgen, L. and Kovac, A. (2006) Extensions of smoothing via taut strings Davies, P. L. (1995) Data features. Statistica Neerlandica 49,185-245.
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2023-06-16 |
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r-spatiotemporal
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Utilities that estimate, predict and cross-validate the spatio-temporal model developed for MESA Air.
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2023-06-16 |
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r-shp2graph
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Functions for converting network data from a SpatialLinesDataFrame object to an 'igraph'-Class object.
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2023-06-16 |
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r-seqmeta
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Computes necessary information to meta analyze region-based tests for rare genetic variants (e.g. SKAT, T1) in individual studies, and performs meta analysis.
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2023-06-16 |
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r-genkern
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Computes generalised KDEs
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2023-06-16 |
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r-smac
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This package provides a solution path for L1-penalized angle-based classification. Three loss functions are implemented in smac, including the deviance loss in logistic regression, the exponential loss in boosting, and the proximal support vector machine loss.
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2023-06-16 |
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r-simone
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Implements the inference of co-expression networks based on partial correlation coefficients from either steady-state or time-course transcriptomic data. Note that with both type of data this package can deal with samples collected in different experimental conditions and therefore not identically distributed. In this particular case, multiple but related networks are inferred on one simone run.
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2023-06-16 |
