An integrated set of tools for thermodynamic calculations in aqueous geochemistry and geobiochemistry. Functions are provided for writing balanced reactions to form species from user-selected basis species and for calculating the standard molal properties of species and reactions, including the standard Gibbs energy and equilibrium constant. Calculations of the non-equilibrium chemical affinity and equilibrium chemical activity of species can be portrayed on diagrams as a function of temperature, pressure, or activity of basis species; in two dimensions, this gives a maximum affinity or predominance diagram. The diagrams have formatted chemical formulas and axis labels, and water stability limits can be added to Eh-pH, oxygen fugacity- temperature, and other diagrams with a redox variable. The package has been developed to handle common calculations in aqueous geochemistry, such as solubility due to complexation of metal ions, mineral buffers of redox or pH, and changing the basis species across a diagram ("mosaic diagrams"). CHNOSZ also implements a group additivity algorithm for the standard thermodynamic properties of proteins.

This package provides methods and utilities for testing, identifying, selecting and mutating objects as categorical or continous types. These functions work on both atomic vectors as well as recursive objects: data.frames, data.tables, tibbles, lists, etc..

This package provides some simple functions for printing text in color in markdown or Quarto documents, to be rendered as HTML or LaTeX. This is useful when writing about the use of colors in graphs or tables, where you want to print their names in their actual color to give a direct impression of the color, like â redâ shown in red, or â blueâ shown in blue.

Joint distribution of number of crossings and the longest run in a series of independent Bernoulli trials. The computations uses an iterative procedure where computations are based on results from shorter series. The procedure conditions on the start value and partitions by further conditioning on the position of the first crossing (or none).

Reconstruct networks from multi-omics data sets with the collaborative graphical lasso (coglasso) algorithm described in Albanese, A., Kohlen, W., and Behrouzi, P. (2024) <doi:10.48550/arXiv.2403.18602>. Use the main wrapper function `bs()` to build and select a multi-omics network.

Psychometrically analyze latent individual differences related to tasks, interventions, or maturational/aging effects in the context of experimental or longitudinal cognitive research using methods first described by Thomas et al. (2020) <doi:10.1177/0013164420919898>.

The Citation File Format version 1.2.0 <doi:10.5281/zenodo.5171937> is a human and machine readable file format which provides citation metadata for software. This package provides core utilities to generate and validate this metadata.

Estimates the causal decompositions of group disparities developed by Yu and Elwert (2025) <doi:10.1214/24-AOAS1990>. For the nuisance functions of the estimators, we provide both parametric and nonparametric options, as well as manual options in case the default models are not satisfying.

The network analysis plays an important role in numerous application domains including biomedicine. Estimation of the number of communities is a fundamental and critical issue in network analysis. Most existing studies assume that the number of communities is known a priori, or lack of rigorous theoretical guarantee on the estimation consistency. This method proposes a regularized network embedding model to simultaneously estimate the community structure and the number of communities in a unified formulation. The proposed model equips network embedding with a novel composite regularization term, which pushes the embedding vector towards its center and collapses similar community centers with each other. A rigorous theoretical analysis is conducted, establishing asymptotic consistency in terms of community detection and estimation of the number of communities. Reference: Ren, M., Zhang S. and Wang J. (2022). "Consistent Estimation of the Number of Communities via Regularized Network Embedding". Biometrics, <doi:10.1111/biom.13815>.

This package implements the nonparametric moving sum procedure for detecting changes in the joint characteristic function (NP-MOJO) for multiple change point detection in multivariate time series. See McGonigle, E. T., Cho, H. (2025) <doi:10.1093/biomet/asaf024> for description of the NP-MOJO methodology.

Subset and download data from EU Copernicus Marine Service Information: <https://data.marine.copernicus.eu>. Import data on the oceans physical and biogeochemical state from Copernicus into R without the need of external software.

Fast C++'-backed tools for computing conspecific and total neighborhood basal area in mapped forest plots. Includes unweighted and distance-weighted neighborhoods, multiple radii, decay kernels, and basic edge correction. Outputs are model-ready covariates for forest competition, growth, and survival models, following neighborhood modeling workflows commonly used in spatial ecology (e.g., Hülsmann et al. 2024 <doi:10.1038/s41586-024-07118-4>).

Download, cache, and manage social contact survey data from the social contact data community on Zenodo (<https://zenodo.org/communities/social_contact_data>) for use in infectious disease modelling. Provides functions to list available surveys, download survey files with automatic caching, and retrieve citations. Contact survey data describe who contacts whom in a population and are used to parameterise age-structured transmission models, for example via the socialmixr package. The surveys available include those from the POLYMOD study (Mossong et al. (2008) <doi:10.1371/journal.pmed.0050074>) and other social contact data shared on Zenodo.

The statistical analysis of circular data using distributions based on symmetric Nonnegative Trigonometric Sums (NNTS). It includes functions to perform empirical analysis and estimate the parameters of density functions. Fernandez-Duran, J.J. and Gregorio-Dominguez, M.M. (2025), "Multimodal Symmetric Circular Distributions Based on Nonnegative Trigonometric Sums and a Likelihood Ratio Test for Reflective Symmetry", <doi:10.48550/arXiv.2412.19501>.

Perform sparse estimation of a Gaussian graphical model (GGM) with node aggregation through variable clustering. Currently, the package implements the clusterpath estimator of the Gaussian graphical model (CGGM) (Touw, Alfons, Groenen & Wilms, 2025; <doi:10.48550/arXiv.2407.00644>).

Nonparametric change point estimation for survival data based on p-values of exact binomial tests.

Core visualizations and summaries for the CRAN package database. The package provides comprehensive methods for cleaning up and organizing the information in the CRAN package database, for building package directives networks (depends, imports, suggests, enhances, linking to) and collaboration networks, producing package dependence trees, and for computing useful summaries and producing interactive visualizations from the resulting networks and summaries. The resulting networks can be coerced to igraph <https://CRAN.R-project.org/package=igraph> objects for further analyses and modelling.

This package implements computationally-efficient construction of confidence intervals from permutation or randomization tests for simple differences in means, based on Nguyen (2009) <doi:10.15760/etd.7798>.

Downloads wrangled Colombian socioeconomic, geospatial,population and climate data from DANE <https://www.dane.gov.co/> (National Administrative Department of Statistics) and IDEAM (Institute of Hydrology, Meteorology and Environmental Studies). It solves the problem of Colombian data being issued in different web pages and sources by using functions that allow the user to select the desired database and download it without having to do the exhausting acquisition process.

This package performs a series of offline and/or online change-point detection algorithms for 1) univariate mean: <doi:10.1214/20-EJS1710>, <arXiv:2006.03283>; 2) univariate polynomials: <doi:10.1214/21-EJS1963>; 3) univariate and multivariate nonparametric settings: <doi:10.1214/21-EJS1809>, <doi:10.1109/TIT.2021.3130330>; 4) high-dimensional covariances: <doi:10.3150/20-BEJ1249>; 5) high-dimensional networks with and without missing values: <doi:10.1214/20-AOS1953>, <arXiv:2101.05477>, <arXiv:2110.06450>; 6) high-dimensional linear regression models: <arXiv:2010.10410>, <arXiv:2207.12453>; 7) high-dimensional vector autoregressive models: <arXiv:1909.06359>; 8) high-dimensional self exciting point processes: <arXiv:2006.03572>; 9) dependent dynamic nonparametric random dot product graphs: <arXiv:1911.07494>; 10) univariate mean against adversarial attacks: <arXiv:2105.10417>.

The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<https://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The cmsafvis R-package provides a collection of R-operators for the analysis and visualization of CM SAF NetCDF data. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).

It computes full conformal, split conformal and multi split conformal prediction regions when the response has functional nature. Moreover, the package also contain a plot function to visualize the output of the split conformal. To guarantee consistency, the package structure mimics the univariate conformalInference package of professor Ryan Tibshirani. The main references for the code are: Diquigiovanni, Fontana, and Vantini (2021) <arXiv:2102.06746>, Diquigiovanni, Fontana, and Vantini (2021) <arXiv:2106.01792>, Solari, and Djordjilovic (2021) <arXiv:2103.00627>.

Implementations of recent complex-valued wavelet shrinkage procedures for smoothing irregularly sampled signals, see Hamilton et al (2018) <doi:10.1080/00401706.2017.1281846>.

This package provides tools for measuring the compositionality of signalling systems (in particular the information-theoretic measure due to Spike (2016) <http://hdl.handle.net/1842/25930> and the Mantel test for distance matrix correlation (after Dietz 1983) <doi:10.1093/sysbio/32.1.21>), functions for computing string and meaning distance matrices as well as an implementation of the Page test for monotonicity of ranks (Page 1963) <doi:10.1080/01621459.1963.10500843> with exact p-values up to k = 22.