This package provides functions related to multivariate measures of independence and ICA: -estimate independent components by minimizing distance covariance; -conduct a test of mutual independence based on distance covariance; -estimate independent components via infomax (a popular method but generally performs poorer than mdcovica, ProDenICA, and/or fastICA, but is useful for comparisons); -order indepedent components by skewness; -match independent components from multiple estimates; -other functions useful in ICA.

This package provides an implementation of Secretary Bird Optimization for general-purpose continuous optimization, benchmark optimization, and training single-hidden-layer feed-forward neural network models. The implemented optimizer is based on the Secretary Bird Optimization Algorithm proposed by Fu et al. (2024) <doi:10.1007/s10462-024-10729-y>. The neural network training functionality is based on Dilber and à zdemir (2026) <doi:10.1007/s00521-026-11874-x>.

Econometric estimation of simultaneous systems of linear and nonlinear equations using Ordinary Least Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted Two-Stage Least Squares (W2SLS), and Three-Stage Least Squares (3SLS) as suggested, e.g., by Zellner (1962) <doi:10.2307/2281644>, Zellner and Theil (1962) <doi:10.2307/1911287>, and Schmidt (1990) <doi:10.1016/0304-4076(90)90127-F>.

If a procedure consists of several stages and there are several models that can be selected for each stage, uncertainty of the procedure can be decomposed by stages or models. This package includes the ANOVA-based method, the cumulative uncertainty-based method, and the balanced decomposition method. Yongdai Kim et al. (2019) <doi:10.1016/j.hydroa.2019.100024> is a related paper which is accessible via the URL below.

Offers a comprehensive set of assertion tests to help users validate the integrity of their data. These tests can be used to check for specific conditions or properties within a dataset and help ensure that data is accurate and reliable. The package is designed to make it easy to add quality control checks to data analysis workflows and to aid in identifying and correcting any errors or inconsistencies in data.

This package provides a visual and interactive web application using RStudio's shiny package. Bad quality samples are detected using sample-dependent and sample-independent controls present on the array and user adjustable thresholds. In depth exploration of bad quality samples can be performed using several interactive diagnostic plots of the quality control probes present on the array. Furthermore, the impact of any batch effect provided by the user can be explored.

This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An "intelligent" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.

This package has been prepared to assist users in computing either a sample size or power value for a microarray experimental study. The user is referred to the cited references for technical background on the methodology underpinning these calculations. This package provides support for five types of sample size and power calculations. These five types can be adapted in various ways to encompass many of the standard designs encountered in practice.

This package provides functions are provided to read and convert AIFF audio files to WAVE (WAV) format. This supports, for example, use of the tuneR package, which does not currently handle AIFF files. The AIFF file format is defined in <https://web.archive.org/web/20080125221040/http://www.borg.com/~jglatt/tech/aiff.htm> and <https://www.mmsp.ece.mcgill.ca/Documents/AudioFormats/AIFF/Docs/AIFF-1.3.pdf> .

Spatial modeling of energy balance and actual evapotranspiration using satellite images and meteorological data. Options of satellite are: Landsat-8 (with and without thermal bands), Sentinel-2 and MODIS. Respectively spatial resolutions are 30, 100, 10 and 250 meters. User can use data from a single meteorological station or a grid of meteorological stations (using any spatial interpolation method). Silva, Teixeira, and Manzione (2019) <doi:10.1016/j.envsoft.2019.104497>.

This package provides tools to compute the center of gravity and moment of inertia tensor of any flying bird. The tools function by modeling a bird as a composite structure of simple geometric objects. This requires detailed morphological measurements of bird specimens although those obtained for the associated paper have been included in the package for use. Refer to the vignettes and supplementary material for detailed information on the package function.

Simulates time-to-event data with type I right censoring using two methods: the inverse CDF method and our proposed memoryless method. The latter method takes advantage of the memoryless property of survival and simulates a separate distribution between change-points. We include two parametric distributions: exponential and Weibull. Inverse CDF method draws on the work of Rainer Walke (2010), <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.

Generate privacy-preserving synthetic datasets that mirror structure, types, factor levels, and missingness; export bundles for LLM workflows (data plus JSON schema and guidance); and build fake data directly from SQL database tables without reading real rows. Methods are related to approaches in Nowok, Raab and Dibben (2016) <doi:10.32614/RJ-2016-019> and the foundation-model overview by Bommasani et al. (2021) <doi:10.48550/arXiv.2108.07258>.

This package provides a nature-inspired metaheuristic algorithm based on the echolocation behavior of microbats that uses frequency tuning to optimize problems in both continuous and discrete dimensions. This R package makes it easy to implement the standard bat algorithm on any user-supplied function. The algorithm was first developed by Xin-She Yang in 2010 (<DOI:10.1007/978-3-642-12538-6_6>, <DOI:10.1109/CINTI.2014.7028669>).

MTrackJ is an ImageJ plugin for motion tracking and analysis (see <https://imagescience.org/meijering/software/mtrackj/>). This package reads and writes MTrackJ Data Files ('.mdf', see <https://imagescience.org/meijering/software/mtrackj/format/>). It supports 2D data and read/writes cluster, point, and channel information. If desired, generates track identifiers that are unique over the clusters. See the project page for more information and examples.

This package provides functions to analyze and visualize meristic, mensural, and categorical phenotypic data in a comparative framework. The package implements an automated pipeline that summarizes traits, identifies diagnostic variables among groups, performs multivariate and univariate statistical analyses, and produces publication-ready graphics. Earlier implementation are described in Torres (2025) <doi:10.64898/2025.12.18.695244> (v1.0.0) and Torres (2026) <doi:10.1002/ece3.73111> (v2.0.0).

Allows the user to convert PDF tables to formats more amenable to analysis ('.csv', .xml', or .xlsx') by wrapping the PDFTables API. In order to use the package, the user needs to sign up for an API account on the PDFTables website (<https://pdftables.com/pdf-to-excel-api>). The package works by taking a PDF file as input, uploading it to PDFTables, and returning a file with the extracted data.

Lightweight, GPU-accelerated bioinformatics visualization widgets (volcano plots, expression and clustered heatmaps, dot plots, stacked violins, embeddings, spatial tissue maps, oncoprints, protein domain lollipops, Kaplan-Meier curves, mutational signature profiles, UpSet plots, treemaps, networks and Hi-C contact matrices) backed by a shared JavaScript core and exposed to R through htmlwidgets'. Designed for large datasets that render smoothly in the browser, the RStudio Viewer, R Markdown, Quarto and Shiny.

Defines functions to describe regression models using only pre-computed summary statistics (i.e. means, variances, and covariances) in place of individual participant data. Possible models include linear models for linear combinations, products, and logical combinations of phenotypes. Implements methods presented in Wolf et al. (2021) <doi:10.3389/fgene.2021.745901> Wolf et al. (2020) <doi:10.1142/9789811215636_0063> and Gasdaska et al. (2019) <doi:10.1142/9789813279827_0036>.

This package provides estimation and inference methods for causal persuasion rates in the potential-outcomes framework of Jun and Lee (2023, Journal of Political Economy) <doi:10.1086/724114>. The package computes bounds and confidence intervals for average and local persuasion rates under data scenarios with binary outcomes, treatments, and instruments, and also when only the outcome and instrument are observed. It also provides functions for calculating bounds from summary statistics.

This package provides tools for generating timed subtitle files and rendering them into video with the FFmpeg command-line interface (<https://ffmpeg.org/>). Converts structured transcription output (such as that produced by Whisper speech-to-text models) into SubRip ('SRT') and Advanced SubStation Alpha ('ASS') subtitle files, with word-level caption timing, styling presets, and line-break control, and burns subtitles into video files using the FFmpeg subtitles filter.

This package provides a toolkit for web scraping, modular NLP pipelines, and text preparation for large language models. Organized around four core actions: fetching, reading, processing, and searching. Covers the full pipeline from raw web data acquisition to structural text processing and BM25 indexing. Supports multiple retrieval strategies including regex, dictionary matching, and ranked keyword search. Pipe-friendly with no heavy dependencies; all outputs are plain data frames or data.tables.

Collaborative writing and editing of R Markdown (or Sweave) documents. The local .Rmd (or .Rnw) is uploaded as a plain-text file to Google Drive. By taking advantage of the easily readable Markdown (or LaTeX) syntax and the well-known online interface offered by Google Docs, collaborators can easily contribute to the writing and editing process. After integrating all authorsâ contributions, the final document can be downloaded and rendered locally.

This package implements a variety of methods for batch correction of single-cell (RNA sequencing) data. This includes methods based on detecting mutually nearest neighbors, as well as several efficient variants of linear regression of the log-expression values. Functions are also provided to perform global rescaling to remove differences in depth between batches, and to perform a principal components analysis that is robust to differences in the numbers of cells across batches.