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r-rrapply
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The minimal 'rrapply'-package contains a single function rrapply(), providing an extended implementation of 'R'-base rapply() by allowing to recursively apply a function to elements of a nested list based on a general condition function and including the possibility to prune or aggregate nested list elements from the result. In addition, special arguments can be supplied to access the name, location, parents and siblings in the nested list of the element under evaluation. The rrapply() function builds upon rapply()'s native 'C' implementation and requires no other package dependencies.
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2025-04-22 |
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r-rseis
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Multiple interactive codes to view and analyze seismic data, via spectrum analysis, wavelet transforms, particle motion, hodograms. Includes general time-series tools, plotting, filtering, interactive display.
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2025-04-22 |
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r-rrcovhd
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Robust multivariate methods for high dimensional data including outlier detection (Filzmoser and Todorov (2013) <doi:10.1016/j.ins.2012.10.017>), robust sparse PCA (Croux et al. (2013) <doi:10.1080/00401706.2012.727746>, Todorov and Filzmoser (2013) <doi:10.1007/978-3-642-33042-1_31>), robust PLS (Todorov and Filzmoser (2014) <doi:10.17713/ajs.v43i4.44>), and robust sparse classification (Ortner et al. (2020) <doi:10.1007/s10618-019-00666-8>).
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2025-04-22 |
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r-rqpen
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Performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to a work in progress vignette.
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2025-04-22 |
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r-round
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Decimal rounding is non-trivial in binary arithmetic. ISO standard round to even is more rare than typically assumed as most decimal fractions are not exactly representable in binary. Our 'roundX()' versions explore differences between current and potential future versions of round() in R. Further, provides (some partly related) C99 math lib functions not in base R.
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2025-04-22 |
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r-rpeglmen
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Implements the fast iterative shrinkage-thresholding algorithm (FISTA) algorithm to fit a Gamma distribution with an elastic net penalty as described in Chen, Arakvin and Martin (2018) <arxiv:1804.07780>. An implementation for the case of the exponential distribution is also available, with details available in Chen and Martin (2018) <https://papers.ssrn.com/abstract_id=3085672>.
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2025-04-22 |
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r-roll
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Fast and efficient computation of rolling and expanding statistics for time-series data.
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2025-04-22 |
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r-roi.plugin.qpoases
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Enhances the 'R' Optimization Infrastructure ('ROI') package with the quadratic solver 'qpOASES'. More information about 'qpOASES' can be found at <https://github.com/coin-or/qpOASES>.
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2025-04-22 |
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r-robustvarcomp
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Robust Estimation of Variance Component Models by classic and composite robust procedures. The composite procedures are robust against outliers generated by the Independent Contamination Model.
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2025-04-22 |
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r-robustlmm
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Implements the Robust Scoring Equations estimator to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.
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2025-04-22 |
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r-robusthd
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Robust methods for high-dimensional data, in particular linear model selection techniques based on least angle regression and sparse regression. Specifically, the package implements robust least angle regression (Khan, Van Aelst & Zamar, 2007; <doi:10.1198/016214507000000950>), (robust) groupwise least angle regression (Alfons, Croux & Gelper, 2016; <doi:10.1016/j.csda.2015.02.007>), and sparse least trimmed squares regression (Alfons, Croux & Gelper, 2013; <doi:10.1214/12-AOAS575>).
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2025-04-22 |
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r-robstattm
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Companion package for the book: "Robust Statistics: Theory and Methods, second edition", <http://www.wiley.com/go/maronna/robust>. This package contains code that implements the robust estimators discussed in the recent second edition of the book above, as well as the scripts reproducing all the examples in the book.
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2025-04-22 |
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r-robust
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public |
Methods for robust statistics, a state of the art in the early 2000s, notably for robust regression and robust multivariate analysis.
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2025-04-22 |
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r-robslopes
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public |
Fast algorithms for the Theil-Sen estimator, Siegel's repeated median slope estimator, and Passing-Bablok regression. The implementation is based on algorithms by Dillencourt et. al (1992) <doi:10.1142/S0218195992000020> and Matousek et. al (1998) <doi:10.1007/PL00009190>. The implementations are detailed in Raymaekers (2023) <doi:10.32614/RJ-2023-012> and Raymaekers J., Dufey F. (2022) <arXiv:2202.08060>. All algorithms run in quasilinear time.
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2025-04-22 |
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r-rniftyreg
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public |
Provides an 'R' interface to the 'NiftyReg' image registration tools <https://github.com/KCL-BMEIS/niftyreg>. Linear and nonlinear registration are supported, in two and three dimensions.
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2025-04-22 |
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r-robcompositions
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Methods for analysis of compositional data including robust methods (<doi:10.1007/978-3-319-96422-5>), imputation of missing values (<doi:10.1016/j.csda.2009.11.023>), methods to replace rounded zeros (<doi:10.1080/02664763.2017.1410524>, <doi:10.1016/j.chemolab.2016.04.011>, <doi:10.1016/j.csda.2012.02.012>), count zeros (<doi:10.1177/1471082X14535524>), methods to deal with essential zeros (<doi:10.1080/02664763.2016.1182135>), (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors, functional data analysis (<doi:10.1016/j.csda.2015.07.007>) and p-splines (<doi:10.1016/j.csda.2015.07.007>), contingency (<doi:10.1080/03610926.2013.824980>) and compositional tables (<doi:10.1111/sjos.12326>, <doi:10.1111/sjos.12223>, <doi:10.1080/02664763.2013.856871>) and (robust) Anderson-Darling normality tests for compositional data as well as popular log-ratio transformations (addLR, cenLR, isomLR, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the ternary diagram.
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2025-04-22 |
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r-rnewsflow
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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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2025-04-22 |
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r-rmvl
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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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2025-04-22 |
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r-rmgarch
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Feasible multivariate GARCH models including DCC, GO-GARCH and Copula-GARCH.
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2025-04-22 |
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r-rle
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Common 'base' and 'stats' methods for 'rle' objects, aiming to make it possible to treat them transparently as vectors.
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2025-04-22 |
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r-rkeops
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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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2025-04-22 |
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r-rioja
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Constrained clustering, transfer functions, and other methods for analysing Quaternary science data.
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2025-04-22 |
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r-rhrv
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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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2025-04-22 |
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r-rgeoda
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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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2025-04-22 |
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r-revdbayes
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Provides functions for the Bayesian analysis of extreme value models. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution. The functionality of 'revdbayes' is similar to the 'evdbayes' package <https://cran.r-project.org/package=evdbayes>, which uses Markov Chain Monte Carlo ('MCMC') methods for posterior simulation. In addition, there are functions for making inferences about the extremal index, using the models for threshold inter-exceedance times of Suveges and Davison (2010) <doi:10.1214/09-AOAS292> and Holesovsky and Fusek (2020) <doi:10.1007/s10687-020-00374-3>. Also provided are d,p,q,r functions for the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') distributions that deal appropriately with cases where the shape parameter is very close to zero.
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2025-04-22 |
