The package contains all the data sets related to the book written by the maintainer of the package.

Various statistical, graphics, and data-management functions used by the Rcmdr package in the R Commander GUI for R.

This package provides an interface to vinecopulib', a C++ library for vine copula modeling. The rvinecopulib package implements the core features of the popular VineCopula package, in particular inference algorithms for both vine copula and bivariate copula models. Advantages over VineCopula are a sleeker and more modern API, improved performances, especially in high dimensions, nonparametric and multi-parameter families, and the ability to model discrete variables. The rvinecopulib package includes vinecopulib as header-only C++ library (currently version 0.7.2). Thus users do not need to install vinecopulib itself in order to use rvinecopulib'. Since their initial releases, vinecopulib is licensed under the MIT License, and rvinecopulib is licensed under the GNU GPL version 3.

Allows the user to conduct randomization-based inference for a wide variety of experimental scenarios. The package leverages a potential outcomes framework to output randomization-based p-values and null intervals for test statistics geared toward any estimands of interest, according to the specified null and alternative hypotheses. Users can define custom randomization schemes so that the randomization distributions are accurate for their experimental settings. The package also creates visualizations of randomization distributions and can test multiple test statistics simultaneously.

The RBP curve is a visual tool to assess the performance of prediction models.

This package contains logic for sample-level variable set scoring using randomized reduced rank reconstruction error. Frost, H. Robert (2023) "Reconstruction Set Test (RESET): a computationally efficient method for single sample gene set testing based on randomized reduced rank reconstruction error" <doi:10.1101/2023.04.03.535366>.

This package provides tools for performing phylogenetic comparative methods for datasets with with multiple observations per species (intraspecific variation or measurement error) and/or missing data (Goolsby et al. 2017). Performs ancestral state reconstruction and missing data imputation on the estimated evolutionary model, which can be specified as Brownian Motion, Ornstein-Uhlenbeck, Early-Burst, Pagel's lambda, kappa, or delta, or a star phylogeny.

Simulates the dynamics of exploited fish populations using the Jones modification of the Beverton-Holt equilibrium yield equation to compute yield-per-recruit and dynamic pool models (Ricker 1975) <https://publications.gc.ca/site/eng/480738/publication.html>. Allows users to evaluate minimum, slot, and inverted length limits on exploited fisheries using specified life history parameters. Users can simulate population under a variety of conditional fishing mortality and conditional natural mortality. Calculated quantities include number of fish harvested and dying naturally, mean weight and length of fish harvested, number of fish that reach specified lengths of interest, total number of fish and biomass in the population, and stock density indices.

Generates tile maps for the East Caucasian language family, inspired by the Typological Atlas of the Languages of Daghestan (TALD, <https://lingconlab.ru/tald/>). It leverages ggplot2 to create visually informative maps, displaying rectangles for each language and allowing for color-coding based on linguistic features. The package includes a built-in dataset of 56 languages and the template for their distribution and provides flexibility to customize the tile map's appearance. The default template can be modified via the ability to hide or rename languages. It's designed to be used with external data tables containing language information and features, offering a tool for visualizing the geographic distribution and linguistic characteristics of East Caucasian languages.

R implementation of SIDES-based subgroup search algorithms (Lipkovich et al. (2017) <doi:10.1002/sim.7064>).

Display spatial data with interactive maps powered by the open- source JavaScript library Leaflet (see <https://leafletjs.com/>). Maps can be rendered in a web browser or displayed in the HTML viewer pane of RStudio'. This package is designed to be easy to use and can create complex maps with vector and raster data, web served map tiles and interface elements.

This package provides a client for (1) querying the DHS API for survey indicators and metadata (<https://api.dhsprogram.com/#/index.html>), (2) identifying surveys and datasets for analysis, (3) downloading survey datasets from the DHS website, (4) loading datasets and associate metadata into R, and (5) extracting variables and combining datasets for pooled analysis.

BaseX <https://basex.org> is a XML database engine and a compliant XQuery 3.1 processor with full support of W3C Update Facility'. This package is a full client-implementation of the client/server protocol for BaseX and provides functionalities to create, manipulate and query on XML-data.

This package contains a collection of helper functions to use with rbi', the R interface to LibBi', described in Murray et al. (2015) <doi:10.18637/jss.v067.i10>. It contains functions to adapt the proposal distribution and number of particles in particle Markov-Chain Monte Carlo, as well as calculating the Deviance Information Criterion (DIC) and converting between times in LibBi results and R time/dates.

Estimating repeatability (intra-class correlation) from Gaussian, binary, proportion and Poisson data.

Electrical properties of resistor networks using matrix methods.

Handle JSON-stat format (<https://json-stat.org>) in R. Not all features are supported, especially the extensive metadata features of JSON-stat'.

This package provides functions for dissimilarity analysis and memory-based learning (MBL, a.k.a local modeling) in complex spectral data sets. Most of these functions are based on the methods presented in Ramirez-Lopez et al. (2013) <doi:10.1016/j.geoderma.2012.12.014>.

This package provides a series of functions to aid in repeated tasks for Rmd documents. All details are to my personal preference, though I am happy to add flexibility if there are use cases I am missing. I will continue updating with new functions as I add utility functions for myself.

An implementation of EDM algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented with Rcpp wrappers around the cppEDM library. It implements the simplex projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the S-map algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, multiview embedding described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.

Simulation of several fractional and multifractional processes. Includes Brownian and fractional Brownian motions, bridges and Gaussian Haar-based multifractional processes (GHBMP). Implements the methods from Ayache, Olenko and Samarakoon (2025) <doi:10.48550/arXiv.2503.07286> for simulation of GHBMP. Estimation of Hurst functions and local fractal dimension. Clustering realisations based on the Hurst functions. Several functions to estimate and plot geometric statistics of the processes and time series. Provides a shiny application for interactive use of the functions from the package.

This package provides functionality to prepare data and analyze plausibility of both forecasted and reported epidemiological signals. The functions implement a set of plausibility algorithms that are agnostic to geographic and time resolutions and are calculated independently then presented as a combined score.

This package provides functions for studying realized genetic relatedness between people. Users will be able to simulate inheritance patterns given pedigree structures, generate SNP marker data given inheritance patterns, and estimate realized relatedness between pairs of individuals using SNP marker data. See Wang (2017) <doi:10.1534/genetics.116.197004>. This work was supported by National Institutes of Health grants R37 GM-046255.

R bindings for functions from the UCR Suite by Rakthanmanon et al. (2012) <DOI:10.1145/2339530.2339576>, which enables ultrafast subsequence search for a best match under Dynamic Time Warping and Euclidean Distance.