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r-rsqlite
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Embeds the 'SQLite' database engine in R and provides an interface compliant with the 'DBI' package. The source for the 'SQLite' engine is included.
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2025-03-25 |
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r-rspectra
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R interface to the 'Spectra' library <https://spectralib.org/> for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n. This package provides the 'eigs()' function that does the similar job as in 'Matlab', 'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function to calculate the largest k singular values and corresponding singular vectors of a real matrix. The matrix to be computed on can be dense, sparse, or in the form of an operator defined by the user.
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2025-03-25 |
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r-robust
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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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2025-03-25 |
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r-rgexf
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Create, read and write GEXF (Graph Exchange XML Format) graph files (used in Gephi and others). Using the XML package, it allows the user to easily build/read graph files including attributes, GEXF viz attributes (such as color, size, and position), network dynamics (for both edges and nodes) and edge weighting. Users can build/handle graphs element-by-element or massively through data-frames, visualize the graph on a web browser through "sigmajs" (a javascript library) and interact with the igraph package.
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2025-03-25 |
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r-ranger
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A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed.
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2025-03-25 |
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r-quantreg
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Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.
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2025-03-25 |
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r-performanceanalytics
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Collection of econometric functions for performance and risk analysis. This package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.
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2025-03-25 |
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r-penalized
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Fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.
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2025-03-25 |
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r-partykit
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A toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ('rpart', 'RWeka', 'PMML') yielding objects that share functionality for print()/plot()/predict() methods. Furthermore, new and improved reimplementations of conditional inference trees (ctree()) and model-based recursive partitioning (mob()) from the 'party' package are provided based on the new infrastructure. A description of this package was published by Hothorn and Zeileis (2015) <http://jmlr.org/papers/v16/hothorn15a.html>.
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2025-03-25 |
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r-pamr
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Some functions for sample classification in microarrays.
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2025-03-25 |
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r-nabor
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An R wrapper for 'libnabo', an exact or approximate k nearest neighbour library which is optimised for low dimensional spaces (e.g. 3D). 'libnabo' has speed and space advantages over the 'ANN' library wrapped by package 'RANN'. 'nabor' includes a knn function that is designed as a drop-in replacement for 'RANN' function nn2. In addition, objects which include the k-d tree search structure can be returned to speed up repeated queries of the same set of target points.
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2025-03-25 |
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r-muhaz
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Produces a smooth estimate of the hazard function for censored data.
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2025-03-25 |
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r-markovchain
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Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided.
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2025-03-25 |
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r-lme4
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Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
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2025-03-25 |
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r-ks
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Kernel smoothers for univariate and multivariate data, including densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two-sample hypothesis tests. Chacon & Duong (2018) <doi:10.1201/9780429485572>.
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2025-03-25 |
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r-influencer
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Provides functionality to compute various node centrality measures on networks. Included are functions to compute betweenness centrality (by utilizing Madduri and Bader's SNAP library), implementations of Burt's constraint and effective network size (ENS) metrics, Borgatti's algorithm to identify key players, and Valente's bridging metric. On Unix systems, the betweenness, Key Players, and bridging implementations are parallelized with OpenMP, which may run faster on systems which have OpenMP configured.
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2025-03-25 |
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r-httpuv
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Provides low-level socket and protocol support for handling HTTP and WebSocket requests directly from within R. It is primarily intended as a building block for other packages, rather than making it particularly easy to create complete web applications using httpuv alone. httpuv is built on top of the libuv and http-parser C libraries, both of which were developed by Joyent, Inc. (See LICENSE file for libuv and http-parser license information.)
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2025-03-25 |
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r-gbm
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An implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway.
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2025-03-25 |
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r-gamlss
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Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.
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2025-03-25 |
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r-dimred
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A collection of dimensionality reduction techniques from R packages and a common interface for calling the methods.
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2025-03-25 |
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r-ddalpha
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Contains procedures for depth-based supervised learning, which are entirely non-parametric, in particular the DDalpha-procedure (Lange, Mosler and Mozharovskyi, 2014 <doi:10.1007/s00362-012-0488-4>). The training data sample is transformed by a statistical depth function to a compact low-dimensional space, where the final classification is done. It also offers an extension to functional data and routines for calculating certain notions of statistical depth functions. 50 multivariate and 5 functional classification problems are included.
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2025-03-25 |
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r-cubist
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Regression modeling using rules with added instance-based corrections.
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2025-03-25 |
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r-ctmcd
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Functions for estimating Markov generator matrices from discrete-time observations. The implemented approaches comprise diagonal adjustment, weighted adjustment and quasi-optimization of matrix logarithm based candidate solutions, an expectation-maximization algorithm as well as a Gibbs sampler.
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2025-03-25 |
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r-classint
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Selected commonly used methods for choosing univariate class intervals for mapping or other graphics purposes.
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2025-03-25 |
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r-bsts
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Time series regression using dynamic linear models fit using MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many other sources.
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2025-03-25 |
