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r-rnewsflow
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public |
A collection of tools for measuring the similarity of text messages and tracing the flow of messages over time and across media.
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2024-01-16 |
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r-robcp
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public |
Provides robust methods to detect change-points in uni- or multivariate time series. They can cope with corrupted data and heavy tails. Focus is on the detection of abrupt changes in location, but changes scale or dependence structure can be detected as well. This package provides tests for change detection in uni- and multivariate time series based on Huberized versions of CUSUM tests proposed in Duerre and Fried (2019) <arXiv:1905.06201>, and tests for change detection in univariate time series based on 2-sample U-statistics or 2-sample U-quantiles as proposed by Dehling et al. (2015) <DOI:10.1007/978-1-4939-3076-0_12> and Dehling, Fried and Wendler (2020) <DOI:10.1093/biomet/asaa004>. Furthermore, the packages provides tests on changes in the scale or the correlation as proposed in Gerstenberger, Vogel and Wendler (2020) <DOI:10.1080/01621459.2019.1629938>, Dehling et al. (2017) <DOI:10.1017/S026646661600044X>, and Wied et al. (2014) <DOI:10.1016/j.csda.2013.03.005>.
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2024-01-16 |
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r-rmvl
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public |
Mappable vector library provides convenient way to access large datasets. Use all of your data at once, with few limits. Memory mapped data can be shared between multiple R processes. Access speed depends on storage medium, so solid state drive is recommended, preferably with PCI Express (or M.2 nvme) interface or a fast network file system. The data is memory mapped into R and then accessed using usual R list and array subscription operators. Convenience functions are provided for merging, grouping and indexing large vectors and data.frames. The layout of underlying MVL files is optimized for large datasets. The vectors are stored to guarantee alignment for vector intrinsics after memory map. The package is built on top of libMVL, which can be used as a standalone C library. libMVL has simple C API making it easy to interchange datasets with outside programs.
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2024-01-16 |
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r-rnomni
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public |
Inverse normal transformation (INT) based genetic association testing. 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, as when the residual distribution exhibits excess skew or kurtosis. Moreover, INT-based tests outperform standard linear regression in terms of power. These tests may be classified into two types. In direct INT (D-INT), the phenotype is itself transformed. In indirect INT (I-INT), phenotypic residuals are transformed. The omnibus test (O-INT) adaptively combines D-INT and I-INT into a single robust and statistically powerful approach. See McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. "Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies" <doi:10.1111/biom.13214>.
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2024-01-16 |
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r-rnifti
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public |
Provides very fast read and write access to images stored in the NIfTI-1, NIfTI-2 and ANALYZE-7.5 formats, with seamless synchronisation of in-memory image objects between compiled C and interpreted R code. Also provides a simple image viewer, and a C/C++ API that can be used by other packages. Not to be confused with 'RNiftyReg', which performs image registration and applies spatial transformations.
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2024-01-16 |
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r-rngwell
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public |
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'', see <doi:10.1145/1132973.1132974>. 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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2024-01-16 |
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r-rngsetseed
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public |
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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2024-01-16 |
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r-rmgarch
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public |
Feasible multivariate GARCH models including DCC, GO-GARCH and Copula-GARCH.
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2024-01-16 |
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r-rnetcdf
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public |
An interface to the 'NetCDF' file formats designed by Unidata for efficient storage of array-oriented scientific data and descriptions. Most capabilities of 'NetCDF' version 4 are supported. Optional conversions of time units are enabled by 'UDUNITS' version 2, also from Unidata.
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2024-01-16 |
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r-rnetcarto
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public |
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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2024-01-16 |
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r-rncl
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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()'.
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2024-01-16 |
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r-rmvp
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public |
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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2024-01-16 |
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r-rmutil
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public |
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 <https://www.commanster.eu/rcode.html>).
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2024-01-16 |
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r-rms
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public |
Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. 'rms' is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. 'rms' works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
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2024-01-16 |
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r-rmpfr
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public |
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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2024-01-16 |
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r-rmr2
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None |
Supports the map reduce programming model on top of hadoop streaming
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2024-01-16 |
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r-rmixtcompio
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public |
Mixture Composer <https://github.com/modal-inria/MixtComp> is a project to build mixture models with heterogeneous data sets and partially missing data management. It includes models for real, categorical, counting, functional and ranking data. This package contains the minimal R interface of the C++ 'MixtComp' library.
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2024-01-16 |
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r-rmkdiscrete
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public |
Sundry discrete probability distributions and helper functions.
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2024-01-16 |
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r-rmixmod
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public |
Interface of 'MIXMOD' software for supervised, unsupervised and semi-supervised classification with mixture modelling <doi: 10.18637/jss.v067.i06>.
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2024-01-16 |
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r-rmi
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public |
Provides mutual information estimators based on k-nearest neighbor estimators by A. Kraskov, et al. (2004) <doi:10.1103/PhysRevE.69.066138>, S. Gao, et al. (2015) <http://proceedings.mlr.press/v38/gao15.pdf> and local density estimators by W. Gao, et al. (2017) <doi:10.1109/ISIT.2017.8006749>.
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2024-01-16 |
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r-rle
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public |
Common 'base' and 'stats' methods for 'rle' objects, aiming to make it possible to treat them transparently as vectors.
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2024-01-16 |
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r-rkeops
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public |
The 'KeOps' library lets you compute generic reductions of very large arrays whose entries are given by a mathematical formula with CPU and GPU computing support. It combines a tiled reduction scheme with an automatic differentiation engine. It is perfectly suited to the efficient computation of Kernel dot products and the associated gradients, even when the full kernel matrix does not fit into the GPU memory.
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2024-01-16 |
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r-rmatio
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public |
Read and write 'Matlab' MAT files from R. The 'rmatio' package supports reading MAT version 4, MAT version 5 and MAT compressed version 5. The 'rmatio' package can write version 5 MAT files and version 5 files with variable compression.
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2024-01-16 |
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r-rmargint
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public |
Three robust marginal integration procedures for additive models based on local polynomial kernel smoothers. As a preliminary estimator of the multivariate function for the marginal integration procedure, a first approach uses local constant M-estimators, a second one uses local polynomials of order 1 over all the components of covariates, and the third one uses M-estimators based on local polynomials but only in the direction of interest. For this last approach, estimators of the derivatives of the additive functions can be obtained. All three procedures can compute predictions for points outside the training set if desired. See Boente and Martinez (2017) <doi:10.1007/s11749-016-0508-0> for details.
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2024-01-16 |
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r-rmalschains
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An implementation of an algorithm family for continuous optimization called memetic algorithms with local search chains (MA-LS-Chains), as proposed in Molina et al. (2010) <doi:10.1162/evco.2010.18.1.18102> and Molina et al. (2011) <doi:10.1007/s00500-010-0647-2>. Rmalschains is further discussed in Bergmeir et al. (2016) <doi:10.18637/jss.v075.i04>. Memetic algorithms are hybridizations of genetic algorithms with local search methods. They are especially suited for continuous optimization.
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2024-01-16 |
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r-rlt
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public |
Random forest with a variety of additional features for regression, classification and survival analysis. The features include: parallel computing with OpenMP, embedded model for selecting the splitting variable, based on Zhu, Zeng & Kosorok (2015) <doi:10.1080/01621459.2015.1036994>, subject weight, variable weight, tracking subjects used in each tree, etc.
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2024-01-16 |
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r-rltp
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public |
R interface to the 'LTP'-Cloud service for Natural Language Processing in Chinese (http://www.ltp-cloud.com/).
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2024-01-16 |
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r-rlrsim
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public |
Rapid, simulation-based exact (restricted) likelihood ratio tests for testing the presence of variance components/nonparametric terms for models fit with nlme::lme(),lme4::lmer(), lmeTest::lmer(), gamm4::gamm4(), mgcv::gamm() and SemiPar::spm().
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2024-01-16 |
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r-rlof
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public |
R parallel implementation of Local Outlier Factor(LOF) which uses multiple CPUs to significantly speed up the LOF computation for large datasets. (Note: The overall performance depends on the computers especially the number of the cores).It also supports multiple k values to be calculated in parallel, as well as various distance measures in addition to the default Euclidean distance.
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2024-01-16 |
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r-rlme
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public |
Estimates robust rank-based fixed effects and predicts robust random effects in two- and three- level random effects nested models. The methodology is described in Bilgic & Susmann (2013) <https://journal.r-project.org/archive/2013/RJ-2013-027/>.
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2024-01-16 |
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r-rlibeemd
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public |
An R interface for libeemd (Luukko, Helske, Räsänen, 2016) <doi:10.1007/s00180-015-0603-9>, a C library of highly efficient parallelizable functions for performing the ensemble empirical mode decomposition (EEMD), its complete variant (CEEMDAN), the regular empirical mode decomposition (EMD), and bivariate EMD (BEMD). Due to the possible portability issues CRAN version no longer supports OpenMP, you can install OpenMP-supported version from GitHub: <https://github.com/helske/Rlibeemd/>.
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2024-01-16 |
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r-rlemon
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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.
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2024-01-16 |
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r-rlabkey
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public |
The 'LabKey' client library for R makes it easy for R users to load live data from a 'LabKey' Server, <https://www.labkey.com/>, into the R environment for analysis, provided users have permissions to read the data. It also enables R users to insert, update, and delete records stored on a 'LabKey' Server, provided they have appropriate permissions to do so.
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2024-01-16 |
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r-rlecuyer
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public |
Provides an interface to the C implementation of the random number generator with multiple independent streams developed by L'Ecuyer et al (2002). The main purpose of this package is to enable the use of this random number generator in parallel R applications.
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2024-01-16 |
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r-rlas
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public |
Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://www.asprs.org/divisions-committees/lidar-division/laser-las-file-format-exchange-activities>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.4 <https://laszip.org/>.
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2024-01-16 |
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r-rioja
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public |
Constrained clustering, transfer functions, and other methods for analysing Quaternary science data.
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2024-01-16 |
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r-rkvo
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public |
This package provides functionality to read files containing observations which consist of arbitrary key/value pairs.
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2024-01-16 |
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r-rjsonio
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None |
This is a package that allows conversion to and from data in Javascript object notation (JSON) format. This allows R objects to be inserted into Javascript/ECMAScript/ActionScript code and allows R programmers to read and convert JSON content to R objects. This is an alternative to rjson package. Originally, that was too slow for converting large R objects to JSON and was not extensible. rjson's performance is now similar to this package, and perhaps slightly faster in some cases. This package uses methods and is readily extensible by defining methods for different classes, vectorized operations, and C code and callbacks to R functions for deserializing JSON objects to R. The two packages intentionally share the same basic interface. This package (RJSONIO) has many additional options to allow customizing the generation and processing of JSON content. This package uses libjson rather than implementing yet another JSON parser. The aim is to support other general projects by building on their work, providing feedback and benefit from their ongoing development.
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2024-01-16 |
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r-rhrv
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public |
Allows users to import data files containing heartbeat positions in the most broadly used formats, to remove outliers or points with unacceptable physiological values present in the time series, to plot HRV data, and to perform time domain, frequency domain and nonlinear HRV analysis. See Garcia et al. (2017) <DOI:10.1007/978-3-319-65355-6>.
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2024-01-16 |
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r-rjson
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None |
Converts R object into JSON objects and vice-versa.
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2024-01-16 |
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r-rje
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public |
A series of functions in some way considered useful to the author. These include methods for subsetting tables and generating indices for arrays, conditioning and intervening in probability distributions, generating combinations, fast transformations, and more...
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2024-01-16 |
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r-rjava
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None |
Low-level interface to Java VM very much like .C/.Call and friends. Allows creation of objects, calling methods and accessing fields.
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2024-01-16 |
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r-rivr
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public |
A tool for undergraduate and graduate courses in open-channel hydraulics. Provides functions for computing normal and critical depths, steady-state water surface profiles (e.g. backwater curves) and unsteady flow computations (e.g. flood wave routing) as described in Koohafkan MC, Younis BA (2015). "Open-channel computation with R." The R Journal, 7(2), 249–262. <doi: 10.32614/RJ-2015-034>.
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2024-01-16 |
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r-riskregression
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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.
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2024-01-16 |
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r-riskparityportfolio
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Fast design of risk parity portfolios for financial investment. The goal of the risk parity portfolio formulation is to equalize or distribute the risk contributions of the different assets, which is missing if we simply consider the overall volatility of the portfolio as in the mean-variance Markowitz portfolio. In addition to the vanilla formulation, where the risk contributions are perfectly equalized subject to no shortselling and budget constraints, many other formulations are considered that allow for box constraints and shortselling, as well as the inclusion of additional objectives like the expected return and overall variance. See vignette for a detailed documentation and comparison, with several illustrative examples. The package is based on the papers: Y. Feng, and D. P. Palomar (2015). SCRIP: Successive Convex Optimization Methods for Risk Parity Portfolio Design. IEEE Trans. on Signal Processing, vol. 63, no. 19, pp. 5285-5300. <doi:10.1109/TSP.2015.2452219>. F. Spinu (2013), An Algorithm for Computing Risk Parity Weights. <doi:10.2139/ssrn.2297383>. T. Griveau-Billion, J. Richard, and T. Roncalli (2013). A fast algorithm for computing High-dimensional risk parity portfolios. <arXiv:1311.4057>.
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2024-01-16 |
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r-rgeoda
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public |
Provides spatial data analysis functionalities including Exploratory Spatial Data Analysis, Spatial Cluster Detection and Clustering Analysis, Regionalization, etc. based on the C++ source code of 'GeoDa', which is an open-source software tool that serves as an introduction to spatial data analysis. The 'GeoDa' software and its documentation are available at <https://geodacenter.github.io>.
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2024-01-16 |
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r-rising
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public |
Fits an Ising model to a binary dataset using L1 regularized logistic regression and extended BIC. Also includes a fast lasso logistic regression function for high-dimensional problems. Uses the 'libLBFGS' optimization library by Naoaki Okazaki.
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2024-01-16 |
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r-rinsp
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public |
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 or length, or proportions. Monte Carlo resampling procedures are available for hypothesis testing against multinomial null models. Details are provided in Zaccarelli et al. (2013) <doi:10.1111/2041-210X.12079> and associated references.
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2024-01-16 |
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r-rinside
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public |
C++ classes to embed R in C++ (and 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. Numerous examples are provided in the nine 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'), 'eigen' (for 'RInside' use with 'RcppEigen'), and 'c_interface' for a basic C interface and 'Ruby' illustration. 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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2024-01-16 |
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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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2024-01-16 |
