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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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2025-04-22 |
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r-rodeo
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Provides an R6 class and several utility methods to facilitate the implementation of models based on ordinary differential equations. The heart of the package is a code generator that creates compiled 'Fortran' (or 'R') code which can be passed to a numerical solver. There is direct support for solvers contained in packages 'deSolve' and 'rootSolve'.
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2025-04-22 |
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r-rodbcext
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An extension for RODBC package adding support for parameterized queries.
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2025-04-22 |
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r-rococo
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Provides the robust gamma rank correlation coefficient as introduced by Bodenhofer, Krone, and Klawonn (2013) <DOI:10.1016/j.ins.2012.11.026> along with a permutation-based rank correlation test. The rank correlation coefficient and the test are explicitly designed for dealing with noisy numerical data.
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2025-04-22 |
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r-robustreg
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Linear regression functions using Huber and bisquare psi functions. Optimal weights are calculated using IRLS algorithm.
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2025-04-22 |
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r-robustgasp
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Robust parameter estimation and prediction of Gaussian stochastic process emulators. It allows for robust parameter estimation and prediction using Gaussian stochastic process emulator. It also implements the parallel partial Gaussian stochastic process emulator for computer model with massive outputs See the reference: Mengyang Gu and Jim Berger, 2016, Annals of Applied Statistics; Mengyang Gu, Xiaojing Wang and Jim Berger, 2018, Annals of Statistics.
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2025-04-22 |
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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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2025-04-22 |
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r-robustetm
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Testing homogeneity for generalized exponential tilt model. This package includes a collection of functions for (1) implementing methods for testing homogeneity for generalized exponential tilt model; and (2) implementing existing methods under comparison.
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2025-04-22 |
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r-robustblme
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Bayesian robust fitting of linear mixed effects models through weighted likelihood equations and approximate Bayesian computation as proposed by Ruli et al. (2017) <arXiv:1706.01752>.
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2025-04-22 |
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r-robustaft
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R functions for the computation of the truncated maximum likelihood and the robust accelerated failure time regression for gaussian and log-Weibull case.
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2025-04-22 |
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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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2025-04-22 |
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r-robfilter
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A set of functions to filter time series based on concepts from robust statistics.
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2025-04-22 |
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r-robeth
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Locations problems, M-estimates of coefficients and scale in linear regression, Weights for bounded influence regression, Covariance matrix of the coefficient estimates, Asymptotic relative efficiency of regression M-estimates, Robust testing in linear models, High breakdown point regression, M-estimates of covariance matrices, M-estimates for discrete generalized linear models.
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2025-04-22 |
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r-robcp
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Provides robust methods to detect change-points in uni- or multivariate time series. They can cope with corrupted data and heavy tails. One can detect changes in location, scale and dependence structure of a possibly multivariate time series. Procedures are based on Huberized versions of CUSUM tests proposed in Duerre and Fried (2019) <arXiv:1905.06201>.
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2025-04-22 |
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r-rnomni
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Genetic association tests that use the rank-based inverse normal transformation (INT). These tests are recommend for continuous traits with non-normally distributed residuals. INT-based tests robustly control the type I error in settings where standard linear regression does not. Moreover, INT-based tests dominate standard linear regression in terms of power. INT-based tests may be classified into two types: tests that directly transform the phenotype (D-INT) and tests that transform phenotypic residuals (I-INT). Our omnibus test (O-INT) adaptively combines D-INT and I-INT into a single robust and statistically powerful approach.
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2025-04-22 |
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r-rnifti
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Provides very fast read and write access to images stored in the NIfTI-1 and ANALYZE-7.5 formats, with seamless synchronisation between compiled C and interpreted R code. Also provides a C/C++ API that can be used by other packages. Not to be confused with 'RNiftyReg', which performs image registration.
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2025-04-22 |
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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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2025-04-22 |
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r-rngwell
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It is a dedicated package to WELL pseudo random generators, which were introduced in Panneton et al. (2006), ``Improved Long-Period Generators Based on Linear Recurrences Modulo 2'', ACM Transactions on Mathematical Software. But this package is not intended to be used directly, you are strongly __encouraged__ to use the 'randtoolbox' package, which depends on this package.
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2025-04-22 |
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r-rngsetseed
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A function setVectorSeed() is provided. Its argument is a numeric vector of an arbitrary nonzero length, whose components have integer values from [0, 2^32-1]. The input vector is transformed using AES (Advanced Encryption Standard) algorithm into an initial state of Mersenne-Twister random number generator. The function provides a better alternative to the R base function set.seed(), if the input vector is a single integer. Initializing a stream of random numbers with a vector is a convenient way to obtain several streams, each of which is identified by several integer indices.
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2025-04-22 |
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r-rnetcdf
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An interface to the NetCDF file format designed by Unidata for efficient storage of array-oriented scientific data and descriptions. The R interface is closely based on the C API of the NetCDF library, and it includes calendar conversions from the Unidata UDUNITS library. The current implementation supports all operations on NetCDF datasets in classic and 64-bit offset file formats, and NetCDF4-classic format is supported for reading and modification of existing files.
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2025-04-22 |
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r-rnetcarto
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It provides functions to compute the modularity and modularity-related roles in networks. It is a wrapper around the rgraph library (Guimera & Amaral, 2005, doi:10.1038/nature03288).
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2025-04-22 |
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r-rmvp
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A memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can (1) effectively process large data, (2) rapidly evaluate population structure, (3) efficiently estimate variance components several algorithms, (4) implement parallel-accelerated association tests of markers three methods, (5) globally efficient design on GWAS process computing, (6) enhance visualization of related information. 'rMVP' contains three models GLM (Alkes Price (2006) <DOI:10.1038/ng1847>), MLM (Jianming Yu (2006) <DOI:10.1038/ng1702>) and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX (Hyunmin Kang (2008) <DOI:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <DOI:10.1038/nmeth.1681>, R implementation from 'GAPIT2': You Tang and Xiaolei Liu (2016) <DOI:10.1371/journal.pone.0107684> and 'SUPER': Qishan Wang and Feng Tian (2014) <DOI:10.1371/journal.pone.0107684>), and HE regression (Xiang Zhou (2017) <DOI:10.1214/17-AOAS1052>).
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2025-04-22 |
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r-rmutil
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A toolkit of functions for nonlinear regression and repeated measurements not to be used by itself but called by other Lindsey packages such as 'gnlm', 'stable', 'growth', 'repeated', and 'event' (available at <http://www.commanster.eu/rcode.html>).
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2025-04-22 |
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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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2025-04-22 |
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r-rmpfr
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Arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental ("special") functions. To this end, the package interfaces to the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library which itself is based on the 'GMP' (GNU Multiple Precision) Library.
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2025-04-22 |
