Generates graphs, CSV files, and coordinates related to river valleys when calling the riverbuilder() function.

This package provides a toolkit for Commodities analytics', risk management and trading professionals. Includes functions for API calls to <https://www.zema.global/platforms/zema-marketplace>, <https://developer.genscape.com/>, and <https://www.bankofcanada.ca/valet/docs>.

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 tools to read various file types into one list of data structures, usually, but not limited to, data frames. Excel files are read sheet-wise, i.e., all or a selection of sheets can be read. Field delimiters and decimal separators are determined automatically.

This package performs Wavelet Lifting Transforms focusing on signal denoising and functional data analysis (FDA). Implements a hybrid architecture with a zero-allocation C++ core for high-performance processing. Features include unified offline (batch) denoising, causal (real-time) filtering using a ring buffer engine, and adaptive recursive thresholding.

This package provides a comprehensive tool for setting up seasonal data pipelines using JDemetra+ (version 3) and rjdverse'. This includes setting up a new working environment, creating and selecting calendar regressors, managing specifications (trading-days regressors and outliers) at the workspace level, making a workspace usable by the cruncher', removing insignificant outliers, and comparing workspaces.

Analyze download logs from the CRAN RStudio mirror (<http://cran.rstudio.com/>). This CRAN mirror is the default one used in RStudio. The available data is the result of parsed and anonymised raw log data from that CRAN mirror.

Estimates and plots as a heat map the rolling window wavelet correlation (RWWC) coefficients statistically significant (within the 95% CI) between two regular (evenly spaced) time series. RolWinWavCor also plots at the same graphic the time series under study. The RolWinWavCor was designed for financial time series, but this software can be used with other kinds of data (e.g., climatic, ecological, geological, etc). The functions contained in RolWinWavCor are highly flexible since these contains some parameters to personalize the time series under analysis and the heat maps of the rolling window wavelet correlation coefficients. Moreover, we have also included a data set (named EU_stock_markets) that contains nine European stock market indices to exemplify the use of the functions contained in RolWinWavCor'. Methods derived from Polanco-Martà nez et al (2018) <doi:10.1016/j.physa.2017.08.065>).

This package provides a resource represents some data or a computation unit. It is described by a URL and credentials. This package proposes a Resource model with "resolver" and "client" classes to facilitate the access and the usage of the resources.

An implementation of robust boosting algorithms for regression in R. This includes the RRBoost method proposed in the paper "Robust Boosting for Regression Problems" (Ju X and Salibian-Barrera M. 2020) <doi:10.1016/j.csda.2020.107065>. It also implements previously proposed boosting algorithms in the simulation section of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) <doi:10.1214/aos/1013203451>) and Robloss (Lutz et al. (2008) <doi:10.1016/j.csda.2007.11.006>).

This package performs two-sample comparisons using the restricted mean survival time (RMST) when survival curves end at different time points between groups. This package implements a sensitivity approach that allows the threshold timepoint tau to be specified after the longest survival time in the shorter survival group. Two kinds of between-group contrast estimators (the difference in RMST and the ratio of RMST) are computed: Uno et al(2014)<doi:10.1200/JCO.2014.55.2208>, Uno et al(2022)<https://CRAN.R-project.org/package=survRM2>, Ueno and Morita(2023)<doi:10.1007/s43441-022-00484-z>.

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>.

Rcpp reimplementation of the the Bayesian non-parametric Dirichlet Process Regression model for penalized regression first published in Zeng and Zhou (2017) <doi:10.1038/s41467-017-00470-2>. A full Bayesian version is implemented with Gibbs sampling, as well as a faster but less accurate variational Bayes approximation.

This package provides tools for generation of (life-history) traits and diversity maps on hexagonal or square grids. Valcu et al.(2012) <doi:10.1111/j.1466-8238.2011.00739.x>.

This package provides a single-function pipeline for automated collapsing and visualization of large phylogenetic trees with geological timescales. Automatically parses taxonomic labels from multiple formats (GTDB, Silva, NCBI, embedded, custom), identifies Most Recent Common Ancestors (MRCAs), assigns color-blind-safe palettes, executes batch collapsing with automatic nesting-aware ordering, integrates deeptime geologic time scales with adaptive time breaks and unit switching, and manages smart legend layout. Supports special ancestral node identifiers (LUCA, LACA, LBCA) for highlighting key nodes in the tree of life. Provides external taxonomy file support for trees with incomplete or missing taxonomic labels. Features real-time logging with timestamps, step tracking, and multiple log levels. Includes comprehensive input validation for tree and sequence file formats. Reduces a 60-line manual workflow to a single function call while preserving full compatibility with the ggtree'/'deeptime ecosystem. The visualization pipeline builds on ggtree Yu et al. (2017) <doi:10.1111/2041-210X.12628>, deeptime Gearty (2025) <doi:10.1080/20964471.2025.2537516>, and ape Paradis and Schliep (2019) <doi:10.1093/bioinformatics/bty633>.

Despite the predominant use of R for data manipulation and various robust statistical calculations, in recent years, more people from various disciplines are beginning to use R for other purposes. In doing this seemlessly, further tools are needed users to easily and freely write in R for all kinds of purposes. The r2dictionary introduces a means for users to directly search for definitions of terms within the R environment.

The lightweight header-only C++-20 logging library spdlite', a lighter version of spdlog and also written by Gabi Melman, provides most of the features of the larger version, and also includes fmt as a fallback if std::format() is not selected.

Build native desktop applications for Windows (with future support planned for macOS and Linux) using R and embedded webviews'. Provides a robust R6'-based event loop, asynchronous background task management via mirai and callr', and a native message bridge for seamless R'-to-user-interface communication without listening ports or network overhead. Allows R developers to create professional, standalone desktop tools with modern web-based user interfaces while maintaining a pure R backend.

This package provides a platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.

This package provides four boolean matrix factorization (BMF) methods. BMF has many applications like data mining and categorical data analysis. BMF is also known as boolean matrix decomposition (BMD) and was found to be an NP-hard (non-deterministic polynomial-time) problem. Currently implemented methods are Asso Miettinen, Pauli and others (2008) <doi:10.1109/TKDE.2008.53>, GreConD R. Belohlavek, V. Vychodil (2010) <doi:10.1016/j.jcss.2009.05.002> , GreConDPlus R. Belohlavek, V. Vychodil (2010) <doi:10.1016/j.jcss.2009.05.002> , topFiberM A. Desouki, M. Roeder, A. Ngonga (2019) <arXiv:1903.10326>.

This package contains functions for simulating the linear fractional stable motion according to the algorithm developed by Mazur and Otryakhin <doi:10.32614/RJ-2020-008> based on the method from Stoev and Taqqu (2004) <doi:10.1142/S0218348X04002379>, as well as functions for estimation of parameters of these processes introduced by Mazur, Otryakhin and Podolskij (2018) <arXiv:1802.06373>, and also different related quantities.

Package of data sets from "Mathematical Statistics with Resampling in R" (1st Ed. 2011, 2nd Ed. 2018) by Laura Chihara and Tim Hesterberg.

This package implements the regularized exponentially tilted empirical likelihood method. Details of the method are given in Kim, MacEachern, and Peruggia (2023) <doi:10.48550/arXiv.2312.17015>. This work was supported by the U.S. National Science Foundation under Grants No. SES-1921523 and DMS-2015552.

Generates polygon straight skeletons and 3D models. Provides functions to create and visualize interior polygon offsets, 3D beveled polygons, and 3D roof models.