Makes it easy to find global administrative boundaries from countries to cities using readable, chainable R syntax. Fetches geometries from Overture Maps Foundation data. Ported from <https://github.com/wherobots/wkls>.

Linguistic Descriptions of Complex Phenomena (LDCP) is an architecture and methodology that allows us to model complex phenomena, interpreting input data, and generating automatic text reports customized to the user needs (see <doi:10.1016/j.ins.2016.11.002> and <doi:10.1007/s00500-016-2430-5>). The proposed package contains a set of methods that facilitates the development of LDCP systems. It main goal is increasing the visibility and practical use of this research line.

Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a ROLAP (Relational On-Line Analytical Processing) star database. The main objective of the package is to allow the definition of these transformations easily. The implementation of the multidimensional database obtained can be exported to work with multidimensional analysis tools on spreadsheets or relational databases.

This package provides functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main references for rSPDE are Bolin, Simas and Xiong (2023) <doi:10.1080/10618600.2023.2231051> for the covariance-based method and Bolin and Kirchner (2020) <doi:10.1080/10618600.2019.1665537> for the operator-based rational approximation. These can be generated by the citation function in R.

Cross-Linguistic Data Format (CLDF) is a framework for storing cross-linguistic data, ensuring compatibility and ease of data exchange between different linguistic datasets see Forkel et al. (2018) <doi:10.1038/sdata.2018.205>. The rcldf package is designed to facilitate the manipulation and analysis of these datasets by simplifying the loading, querying, and visualisation of CLDF datasets making it easier to conduct comparative linguistic analyses, manage language data, and apply statistical methods directly within R.

Convex Least Squares Programming (CLSP) is a two-step estimator for solving underdetermined, ill-posed, or structurally constrained least-squares problems. It combines pseudoinverse-based estimation with convex-programming correction methods inspired by Lasso, Ridge, and Elastic Net to ensure numerical stability, constraint enforcement, and interpretability. The package also provides numerical stability analysis and CLSP-specific diagnostics, including partial R^2, normalized RMSE (NRMSE), Monte Carlo t-tests for mean NRMSE, and condition-number-based confidence bands.

Create, read and write GEXF (Graph Exchange XML Format) graph files (used in Gephi and others). It allows the user to easily build/read graph files including attributes, GEXF visual attributes (such as color, size, and position), network dynamics (for both edges and nodes) and edge weighting. Users can build/handle graphs element-by-element or massively through data-frames, visualize the graph on a web browser through gexf-js (a JavaScript library) and interact with the igraph package.

Point and interval estimation of linear parameters with data obtained from complex surveys (including stratified and clustered samples) when randomization techniques are used. The randomized response technique was developed to obtain estimates that are more valid when studying sensitive topics. Estimators and variances for 14 randomized response methods for qualitative variables and 7 randomized response methods for quantitative variables are also implemented. In addition, some data sets from surveys with these randomization methods are included in the package.

This package provides tools for estimating variance-mean dependence in count data from high-throughput genetic sequencing assays and for testing for differential expression based on a model using the negative binomial distribution.

This is a package for multivariate data analysis and graphical display of microarray data. Functions are included for supervised dimension reduction (between group analysis) and joint dimension reduction of two datasets (coinertia analysis).

Many models contain tuning parameters (i.e. parameters that cannot be directly estimated from the data). These tools can be used to define objects for creating, simulating, or validating values for such parameters.

This package provides a collection of efficient, vectorized algorithms for the creation and investigation of magic squares and hypercubes, including a variety of functions for the manipulation and analysis of arbitrarily dimensioned arrays.

This package provides tools to compute Gower's distance (or similarity) coefficient between records, and to compute the top-n matches between records. Core algorithms are executed in parallel on systems supporting OpenMP.

Compare complex R objects and reveal the key differences. This package was designed particularly for use in testing packages where being able to quickly isolate key differences makes understanding test failures much easier.

This package checks adherence to a given style, syntax errors and possible semantic issues. It supports on the fly checking of R code edited with RStudio IDE, Emacs and Vim.

This package provides a simple set of wrapper functions for data.table::fread() that allows subsetting or filtering rows and selecting columns of table-formatted files too large for the available RAM.

rpatool is a simple tool allowing you to create, modify and extract Ren'Py Archive files (.rpa/.rpi). Currently, only writing RPAv2/RPAv3 archives is supported.

This package provides the asynchronous RPC client-server framework and message specification for Rigetti Quantum Cloud Services (QCS). It implements an efficient transport protocol by using ZeroMQ (ZMQ) sockets and MessagePack (msgpack) serialization.

TTMap is a clustering method that groups together samples with the same deviation in comparison to a control group. It is specially useful when the data is small. It is parameter free.

Which day a week starts depends heavily on the either the local or professional context. This package is designed to be a lightweight solution to easily switching between week-based date definitions.

Enables the user to infer potential synthetic lethal relationships by analysing relationships between bimodally distributed gene pairs in big gene expression datasets. Enables the user to visualise these candidate synthetic lethal relationships.

Easily processes batches of univariate or multivariate regression models. Returns results in a tidy format and generates visualization plots for straightforward interpretation (Wang, Shixiang, et al. (2025) <DOI:10.1002/mdr2.70028>).

Implementation of the Cluster Estimated Standard Errors (CESE) proposed in Jackson (2020) <DOI:10.1017/pan.2019.38> to compute clustered standard errors of linear coefficients in regression models with grouped data.

Allows Brownian motion, fractional Brownian motion, and integrated Ornstein-Uhlenbeck process components to be added to linear and non-linear mixed effects models using the structures and methods of the nlme package.