This package provides tools for generating descriptives and report tables for different models, data.frames and tables and exporting them to different formats.

Scalable implementation of classification and regression forests, as described by Breiman (2001), <DOI:10.1023/A:1010933404324>.

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>.

Extends the functionality of the RTMB <https://kaskr.r-universe.dev/RTMB> package by providing a collection of non-standard probability distributions compatible with automatic differentiation (AD). While RTMB enables flexible and efficient modelling, including random effects, its built-in support is limited to standard distributions. The package adds additional AD-compatible distributions, broadening the range of models that can be implemented and estimated using RTMB'. Automatic differentiation and Laplace approximation are described in Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>.

This package provides a single method implementing multiple approaches to generate pseudo-random vectors whose components sum up to one (see, e.g., Maziero (2015) <doi:10.1007/s13538-015-0337-8>). The components of such vectors can for example be used for weighting objectives when reducing multi-objective optimisation problems to a single-objective problem in the socalled weighted sum scalarisation approach.

These tools were created to test map-scale hypotheses about trends in large remotely sensed data sets but any data with spatial and temporal variation can be analyzed. Tests are conducted using the PARTS method for analyzing spatially autocorrelated time series (Ives et al., 2021: <doi:10.1016/j.rse.2021.112678>). The method's unique approach can handle extremely large data sets that other spatiotemporal models cannot, while still appropriately accounting for spatial and temporal autocorrelation. This is done by partitioning the data into smaller chunks, analyzing chunks separately and then combining the separate analyses into a single, correlated test of the map-scale hypotheses.

This package provides functions to manipulate rational functions, including basic arithmetic operators, derivatives, and integrals with EXPLICIT forms.

An extremely simple stack data type, implemented with R6 classes. The size of the stack increases as needed, and the amortized time complexity is O(1). The stack may contain arbitrary objects.

This package provides functions for phylogenetic analysis (Castiglione et al., 2018 <doi:10.1111/2041-210X.12954>). The functions perform the estimation of phenotypic evolutionary rates, identification of phenotypic evolutionary rate shifts, quantification of direction and size of evolutionary change in multivariate traits, the computation of ontogenetic shape vectors and test for morphological convergence.

Fast tools for unequal probability sampling in multi-dimensional spaces, implemented in Rust for high performance. The package offers a wide range of methods, including Sampford (Sampford, 1967, <doi:10.1093/biomet/54.3-4.499>) and correlated Poisson sampling (Bondesson and Thorburn, 2008, <doi:10.1111/j.1467-9469.2008.00596.x>), pivotal sampling (Deville and Tillé, 1998, <doi:10.1093/biomet/91.4.893>), and balanced sampling such as the cube method (Deville and Tillé, 2004, <doi:10.1093/biomet/91.4.893>) to ensure auxiliary totals are respected. Spatially balanced approaches, including the local pivotal method (Grafström et al., 2012, <doi:10.1111/j.1541-0420.2011.01699.x>), spatially correlated Poisson sampling (Grafström, 2012, <doi:10.1016/j.jspi.2011.07.003>), and locally correlated Poisson sampling (Prentius, 2024, <doi:10.1002/env.2832>), provide efficient designs when the target variable is linked to auxiliary information.

This package provides a platform-independent GUI for design of experiments. The package is implemented as a plugin to the R-Commander, which is a more general graphical user interface for statistics in R based on tcl/tk. DoE functionality can be accessed through the menu Design that is added to the R-Commander menus.

Interface to the UNU.RAN library for Universal Non-Uniform RANdom variate generators. Thus it allows to build non-uniform random number generators from quite arbitrary distributions. In particular, it provides an algorithm for fast numerical inversion for distribution with given density function. In addition, the package contains densities, distribution functions and quantiles from a couple of distributions.

Provide function for get data from YouTube Data API <https://developers.google.com/youtube/v3/docs/>, YouTube Analytics API <https://developers.google.com/youtube/analytics/reference/> and YouTube Reporting API <https://developers.google.com/youtube/reporting/v1/reports>.

Generate, simulate and visualise ODE models of consumer-resource interactions. At its core, rescomp provides a resource competition modelling focused interface to deSolve', alongside flexible functions for visualising model properties and dynamics. More information, documentation and examples can be found on the package website.

Connection to the Redis (or Valkey') key/value store using the C-language client library hiredis (included as a fallback) with MsgPack encoding provided via RcppMsgPack headers. It now also includes the pub/sub functions from the rredis package.

Robust tail dependence estimation for bivariate models. This package is based on two papers by the authors:'Robust and bias-corrected estimation of the coefficient of tail dependence and Robust and bias-corrected estimation of probabilities of extreme failure sets'. This work was supported by a research grant (VKR023480) from VILLUM FONDEN and an international project for scientific cooperation (PICS-6416).

This package implements the "Stemming Algorithm for the Portuguese Language" <DOI:10.1109/SPIRE.2001.10024>.

Interoperability between Rcpp and the C++11 array and tuple types. Linking to this package allows fixed-length std::array objects to be converted to and from equivalent R vectors, and std::tuple objects converted to lists, via the as() and wrap() functions. There is also experimental support for std::span from C++20'.

Nonparametric maximum likelihood estimation methods for random coefficient binary response models and some related functionality for sequential processing of hyperplane arrangements. See J. Gu and R. Koenker (2020) <DOI:10.1080/01621459.2020.1802284>.

Reads data files acquired by Bruker Daltonics matrix-assisted laser desorption/ionization-time-of-flight mass spectrometer of the *flex series.

Offers a suite of tools designed to enhance the responsiveness and interactivity of web-based documents and applications created with R. It provides an automatic, configurable resizing toolbar that can be seamlessly integrated with HTML elements such as containers, images, and tables, allowing end-users to dynamically adjust their dimensions. Beyond the toolbar, the package includes a rich collection of flexible, expandable, and interactive container functionalities, such as highly customizable split-screen layouts (splitCard), versatile sizeable cards (sizeableCard), dynamic window-like elements (windowCard), visually engaging emphasis cards (empahsisCard), and sophisticated flexible and elastic card layouts (flexCard, elastiCard). Furthermore, it offers an elegant image viewer and resizer (shinyExpandImage) perfect for interactive galleries. r2resize is particularly well-suited for developers and data scientists looking to create modern, responsive, and user-friendly shiny applications, markdown reports, and quarto documents that adapt gracefully to different screen sizes and user preferences, significantly improving the user experience.

Tool for the analysis Mass Spectrometry (MS) data in the context of immunopeptidomic analysis for the identification of hybrid peptides and the predictions of binding affinity of all peptides using netMHCpan <doi:10.1093/nar/gkaa379> while providing a summary of the netMHCpan output. RHybridFinder (RHF) is destined for researchers who are looking to analyze their MS data for the purpose of identification of potential spliced peptides. This package, developed mainly in base R, is based on the workflow published by Faridi et al. in 2018 <doi:10.1126/sciimmunol.aar3947>.

This package provides a programmatic interface to the Web Service methods provided by ITALIC (<https://italic.units.it>). ITALIC is a database of lichen data in Italy and bordering European countries. ritalic includes functions for retrieving information about lichen scientific names, geographic distribution, ecological data, morpho-functional traits and identification keys. More information about the data is available at <https://italic.units.it/?procedure=base&t=59&c=60>. The API documentation is available at <https://italic.units.it/?procedure=api>.

Queries data from WHOIS servers.