Automated performance of common transformations used to fulfill parametric assumptions of normality and identification of the best performing method for the user. Output for various normality tests (Thode, 2002) corresponding to the best performing method and a descriptive statistical report of the input data in its original units (5-number summary and mathematical moments) are also presented. Lastly, the Rankit, an empirical normal quantile transformation (ENQT) (Soloman & Sawilowsky, 2009), is provided to accommodate non-standard use cases and facilitate adoption. <DOI: 10.1201/9780203910894>. <DOI: 10.22237/jmasm/1257034080>.

This package creates and maintains a build process for complex analytic tasks in R. Package allows to easily generate Makefile for the (GNU) make tool, which drives the build process by (in parallel) executing build commands in order to update results accordingly to given dependencies on changed data or updated source files.

This package provides a collection of functions to estimate Rogers-Castro migration age schedules using Stan'. This model which describes the fundamental relationship between migration and age in the form of a flexible multi-exponential migration model was most notably proposed in Rogers and Castro (1978) <doi:10.1068/a100475>.

This package provides functions to handle command-line arguments for R scripting. It enables building stand-alone R programs that accept and parse command-line options in BIOS style. Zhang (2025) <https://github.com/bedapub/ribiosArg>.

This package implements an objective Bayes intrinsic conditional autoregressive prior. This model provides an objective Bayesian approach for modeling spatially correlated areal data using an intrinsic conditional autoregressive prior on a vector of spatial random effects.

Three robust marginal integration procedures for additive models based on local polynomial kernel smoothers. As a preliminary estimator of the multivariate function for the marginal integration procedure, a first approach uses local constant M-estimators, a second one uses local polynomials of order 1 over all the components of covariates, and the third one uses M-estimators based on local polynomials but only in the direction of interest. For this last approach, estimators of the derivatives of the additive functions can be obtained. All three procedures can compute predictions for points outside the training set if desired. See Boente and Martinez (2017) <doi:10.1007/s11749-016-0508-0> for details.

Assists in the whole process of designing and evaluating Randomized Control Trials. Robust treatment assignment by strata/blocks, that handles misfits; Power calculations of the minimum detectable treatment effect or minimum populations; Balance tables of T-test of covariates; Balance Regression: (treatment ~ all x variables) with F-test of null model; Impact_evaluation: Impact evaluation regressions. This function gives you the option to include control_vars, fixed effect variables, cluster variables (for robust SE), multiple endogenous variables and multiple heterogeneous variables (to test treatment effect heterogeneity) summary_statistics: Function that creates a summary statistics table with statistics rank observations in n groups: Creates a factor variable with n groups. Each group has a min and max label attach to each category. Athey, Susan, and Guido W. Imbens (2017) <arXiv:1607.00698>.

Conversion between attitude representations: DCM, Euler angles, Quaternions, and Euler vectors. Plus conversion between 2 Euler angle set types (xyx, yzy, zxz, xzx, yxy, zyz, xyz, yzx, zxy, xzy, yxz, zyx). Fully vectorized code, with warnings/errors for Euler angles (singularity, out of range, invalid angle order), DCM (orthogonality, not proper, exceeded tolerance to unity determinant) and Euler vectors(not unity). Also quaternion and other useful functions. Based on SpinCalc by John Fuller and SpinConv by Paolo de Leva.

The RcppClassic package provides a deprecated C++ library which facilitates the integration of R and C++. New projects should use the new Rcpp API in the Rcpp package.

Risk-related information (like the prevalence of conditions, the sensitivity and specificity of diagnostic tests, or the effectiveness of interventions or treatments) can be expressed in terms of frequencies or probabilities. By providing a toolbox of corresponding metrics and representations, riskyr computes, translates, and visualizes risk-related information in a variety of ways. Adopting multiple complementary perspectives provides insights into the interplay between key parameters and renders teaching and training programs on risk literacy more transparent (see <doi:10.3389/fpsyg.2020.567817>, for details).

This package provides a very lightweight package that writes out log messages in an opinionated way. Simpler and lighter than other logging packages, rlog provides a compact feature set that focuses on getting the job done in a Unix-like way.

This package provides methods for comparing different regression algorithms for describing the temporal dynamics of secondary tree growth (xylem and phloem). Users can compare the accuracy of the most common fitting methods usually used to analyse xylem and phloem data, i.e., Gompertz function, Double Gompertz function, General Additive Models (GAMs); and an algorithm newly introduced to the field, i.e., Bayesian Regularised Neural Networks (brnn). The core function of the package is XPSgrowth(), while the results can be interpreted using implemented generic S3 methods, such as plot() and summary().

This package provides a set of functions to simplify reading data from files. The main function, reader(), should read most common R datafile types without needing any parameters except the filename. Other functions provide simple ways of handling file paths and extensions, and automatically detecting file format and structure.

This package provides a simple set of wrappers to easily use RDCOMClient for generating Microsoft PowerPoint presentations. Warning:this package is soon to be archived from CRAN.

Quickly imports, processes, analyzes, and visualizes mass-spectrometric data. Includes functions for easily extracting specific data and measurements from large (multi-gigabyte) raw Bruker data files, as well as a set of S3 object classes for manipulating and measuring mass spectrometric peaks and plotting peaks and spectra using the ggplot2 package.

Allows the user to implement a dark/light toggle mode in shiny using the Nightly JavaScript library. The default mode is dark/light however the user can also specify other colours.

The Regional Vulnerability Index (RVI), a statistical measure of brain structural abnormality, quantifies an individual's similarity to the expected pattern (effect size) of deficits in schizophrenia (Kochunov P, Fan F, Ryan MC, et al. (2020) <doi:10.1002/hbm.25045>).

This package provides a set of functions to perform pathway analysis and meta-analysis from multiple gene expression datasets, as well as visualization of the results. This package wraps functionality from the following packages: Ritchie et al. (2015) <doi:10.1093/nar/gkv007>, Love et al. (2014) <doi:10.1186/s13059-014-0550-8>, Robinson et al. (2010) <doi:10.1093/bioinformatics/btp616>, Korotkevich et al. (2016) <arxiv:10.1101/060012>, Efron et al. (2015) <https://CRAN.R-project.org/package=GSA>, and Gu et al. (2012) <https://CRAN.R-project.org/package=CePa>.

This package provides a task-oriented R interface to the RDKit <https://www.rdkit.org> library through its Python API via reticulate'. The package offers high-level cheminformatics functionality, including molecule parsing, descriptor calculation, and fingerprint generation without replicating the native structure of RDKit'.

This package provides a solution path for Reinforced Angle-based Multicategory Support Vector Machines, with linear learning, polynomial learning, and Gaussian kernel learning. C. Zhang, Y. Liu, J. Wang and H. Zhu. (2016) <doi:10.1080/10618600.2015.1043010>.

Sample size and confidence interval calculations in reversible catalytic models, with applications in malaria research. Further details can be found in the paper by Sepúlveda and Drakeley (2015, <doi:10.1186/s12936-015-0661-z>).

The TRUST4 or MiXCR is used to identify the clonotypes. The goal of rTCRBCRr is to process the results from these clonotyping tools, and analyze the clonotype repertoire metrics based on chain names and IGH isotypes. The manuscript is still under preparation for publication for now. The references describing the methods in this package will be added later.

This package provides tools for implementing Retrieval-Augmented Generation (RAG) workflows with Large Language Models (LLM). Includes functions for document processing, text chunking, embedding generation, storage management, and content retrieval. Supports various document types and embedding providers ('Ollama', OpenAI'), with DuckDB as the default storage backend. Integrates with the ellmer package to equip chat objects with retrieval capabilities. Designed to offer both sensible defaults and customization options with transparent access to intermediate outputs. For a review of retrieval-augmented generation methods, see Gao et al. (2023) "Retrieval-Augmented Generation for Large Language Models: A Survey" <doi:10.48550/arXiv.2312.10997>.

Inference of relatedness coefficients from a bi-allelic genotype matrix using a Maximum Likelihood estimation, Laporte, F., Charcosset, A. and Mary-Huard, T. (2017) <doi:10.1111/biom.12634>.