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r-word2vec
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Learn vector representations of words by continuous bag of words and skip-gram implementations of the 'word2vec' algorithm. The techniques are detailed in the paper "Distributed Representations of Words and Phrases and their Compositionality" by Mikolov et al. (2013), available at <arXiv:1310.4546>.
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2025-04-22 |
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r-winch
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Obtain the native stack trace and fuse it with R's stack trace for easier debugging of R packages with native code.
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2025-04-22 |
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r-weightsvm
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Functions for subject/instance weighted support vector machines (SVM). It uses a modified version of 'libsvm' and is compatible with package 'e1071'. It also allows user defined kernel matrix.
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2025-04-22 |
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r-webfakes
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Create a web app that makes it easier to test web clients without using the internet. It includes a web app framework with path matching, parameters and templates. Can parse various 'HTTP' request bodies. Can send 'JSON' data or files from the disk. Includes a web app that implements the 'httpbin.org' web service.
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2025-04-22 |
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r-weights
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Provides a variety of functions for producing simple weighted statistics, such as weighted Pearson's correlations, partial correlations, Chi-Squared statistics, histograms, and t-tests. Also now includes some software for quickly recoding survey data and plotting estimates from interaction terms in regressions (and multiply imputed regressions) both with and without weights. NOTE: Weighted partial correlation calculations pulled to address a bug.
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2025-04-22 |
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r-warp
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Tooling to group dates by a variety of periods including: yearly, monthly, by second, by week of the month, and more. The groups are defined in such a way that they also represent the distance between dates in terms of the period. This extracts valuable information that can be used in further calculations that rely on a specific temporal spacing between observations.
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2025-04-22 |
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r-warbler
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Functions aiming to facilitate the analysis of the structure of animal acoustic signals in 'R'. 'warbleR' makes use of the basic sound analysis tools from the package 'seewave', and offers new tools for acoustic structure analysis. The main features of the package are the use of loops to apply tasks through acoustic signals referenced in a selection (annotation) table and the production of spectrograms in image files that allow to organize data and verify acoustic analyzes. The package offers functions to explore, organize and manipulate multiple sound files, explore and download 'Xeno-Canto' recordings, detect signals automatically, create spectrograms of complete recordings or individual signals, run different measures of acoustic signal structure, evaluate the performance of measurement methods, catalog signals, characterize different structural levels in acoustic signals, run statistical analysis of duet coordination and consolidate databases and annotation tables, among others.
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2025-04-22 |
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r-vim
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New tools for the visualization of missing and/or imputed values are introduced, which can be used for exploring the data and the structure of the missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods may help to identify the mechanism generating the missing values and allows to explore the data including missing values. In addition, the quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot methods. A graphical user interface available in the separate package VIMGUI allows an easy handling of the implemented plot methods.
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2025-04-22 |
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r-vinecopula
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Provides tools for the statistical analysis of regular vine copula models, see Aas et al. (2009) <doi:10.1016/j.insmatheco.2007.02.001> and Dissman et al. (2013) <doi:10.1016/j.csda.2012.08.010>. The package includes tools for parameter estimation, model selection, simulation, goodness-of-fit tests, and visualization. Tools for estimation, selection and exploratory data analysis of bivariate copula models are also provided.
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2025-04-22 |
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r-vdiffr
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An extension to the 'testthat' package that makes it easy to add graphical unit tests. It provides a Shiny application to manage the test cases.
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2025-04-22 |
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r-vegan
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Ordination methods, diversity analysis and other functions for community and vegetation ecologists.
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2025-04-22 |
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r-vcfr
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Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software.
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2025-04-22 |
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r-validate
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Declare data validation rules and data quality indicators; confront data with them and analyze or visualize the results. The package supports rules that are per-field, in-record, cross-record or cross-dataset. Rules can be automatically analyzed for rule type and connectivity. Supports checks implied by an SDMX DSD file as well. See also Van der Loo and De Jonge (2018) <doi:10.1002/9781118897126>, Chapter 6 and the JSS paper (2021) <doi:10.18637/jss.v097.i10>.
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2025-04-22 |
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r-ubl
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Provides a set of functions that can be used to obtain better predictive performance on cost-sensitive and cost/benefits tasks (for both regression and classification). This includes re-sampling approaches that modify the original data set biasing it towards the user preferences.
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2025-04-22 |
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r-tweenr
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In order to create smooth animation between states of data, tweening is necessary. This package provides a range of functions for creating tweened data that can be used as basis for animation. Furthermore it adds a number of vectorized interpolaters for common R data types such as numeric, date and colour.
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2025-04-22 |
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r-twang
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Provides functions for propensity score estimating and weighting, nonresponse weighting, and diagnosis of the weights.
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2025-04-22 |
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r-truncatednormal
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A collection of functions to deal with the truncated univariate and multivariate normal and Student distributions, described in Botev (2017) <doi:10.1111/rssb.12162> and Botev and L'Ecuyer (2015) <doi:10.1109/WSC.2015.7408180>.
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2025-04-22 |
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r-trend
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The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.
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2025-04-22 |
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r-treedist
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Implements measures of tree similarity, including information-based generalized Robinson-Foulds distances (Phylogenetic Information Distance, Clustering Information Distance, Matching Split Information Distance; Smith 2020) <doi:10.1093/bioinformatics/btaa614>; Jaccard-Robinson-Foulds distances (Bocker et al. 2013) <doi:10.1007/978-3-642-40453-5_13>, including the Nye et al. (2006) metric <doi:10.1093/bioinformatics/bti720>; the Matching Split Distance (Bogdanowicz & Giaro 2012) <doi:10.1109/TCBB.2011.48>; Maximum Agreement Subtree distances; the Kendall-Colijn (2016) distance <doi:10.1093/molbev/msw124>, and the Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. (1996) <doi:10.1007/3-540-61332-3_168>. Includes tools for visualizing mappings of tree space (Smith 2022) <doi:10.1093/sysbio/syab100>, for calculating the median of sets of trees, and for computing the information content of trees and splits.
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2025-04-22 |
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r-tree.interpreter
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An R re-implementation of the 'treeinterpreter' package on PyPI <https://pypi.org/project/treeinterpreter/>. Each prediction can be decomposed as 'prediction = bias + feature_1_contribution + ... + feature_n_contribution'. This decomposition is then used to calculate the Mean Decrease Impurity (MDI) and Mean Decrease Impurity using out-of-bag samples (MDI-oob) feature importance measures based on the work of Li et al. (2019) <arXiv:1906.10845>.
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2025-04-22 |
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r-traminer
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Set of sequence analysis tools for manipulating, describing and rendering categorical sequences, and more generally mining sequence data in the field of social sciences. Although this sequence analysis package is primarily intended for state or event sequences that describe time use or life courses such as family formation histories or professional careers, its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for converting sequences from one format to another. It offers several functions for describing and rendering sequences, for computing distances between sequences with different metrics (among which optimal matching), original dissimilarity-based analysis tools, and functions for extracting the most frequent event subsequences and identifying the most discriminating ones among them. A user's guide can be found on the TraMineR web page.
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2025-04-22 |
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r-tram
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Formula-based user-interfaces to specific transformation models implemented in package 'mlt'. Available models include Cox models, some parametric survival models (Weibull, etc.), models for ordered categorical variables, normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression (Lohse et al., 2017, <DOI:10.12688/f1000research.12934.1>). The underlying theory is described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>. An extension to transformation models for clustered data is provided (Barbanti and Hothorn, 2022, <DOI:10.1093/biostatistics/kxac048>). Multivariate conditional transformation models (Klein et al, 2022, <DOI:10.1111/sjos.12501>) and shift-scale transformation models (Siegfried et al, 2023, <DOI:10.1080/00031305.2023.2203177>) can be fitted as well.
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2025-04-22 |
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r-transformr
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In order to smoothly animate the transformation of polygons and paths, many aspects needs to be taken into account, such as differing number of control points, changing center of rotation, etc. The 'transformr' package provides an extensive framework for manipulating the shapes of polygons and paths and can be seen as the spatial brother to the 'tweenr' package.
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2025-04-22 |
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r-torch
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Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.
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2025-04-22 |
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r-tmvtnorm
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Random number generation for the truncated multivariate normal and Student t distribution. Computes probabilities, quantiles and densities, including one-dimensional and bivariate marginal densities. Computes first and second moments (i.e. mean and covariance matrix) for the double-truncated multinormal case.
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2025-04-22 |
