Mimic the style of traditional reporting macros for clinical trials. The purpose is to generate tables, listings and figures that support clinical research. This package is well suited for firms or individuals who wish to incorporate R without changing their ways of working as it follows a traditional clinical research workflow. Invoke functions (instead of macros) to summarize data and produce formatted reports. This package differs from others in that it includes tools (wrappers) for both analyzing and reporting data.

Developed to assist researchers with planning analysis, prior to obtaining data from Trusted Research Environments (TREs) also known as safe havens. With functionality to export and import marginal distributions as well as synthesise data, both with and without correlations from these marginal distributions. Using a multivariate cumulative distribution (COPULA). Additionally the International Stroke Trial (IST) is included as an example dataset under ODC-By licence Sandercock et al. (2011) <doi:10.7488/ds/104>, Sandercock et al. (2011) <doi:10.1186/1745-6215-12-101>.

This package provides a colour list and colour metric based on the ISCC-NBS System of Color Designation for use with the roloc package for converting colour specifications to colour names.

The Google FarmHash family of hash functions is used by the Google BigQuery data warehouse via the FARM_FINGERPRINT function. This package permits to calculate these hash digest fingerprints directly from R, and uses the included FarmHash files written by G. Pike and copyrighted by Google, Inc.

This package provides a parallel function for multivariate outlier detection named modified Stahel-Donoho estimators is contained in this package. The function RMSDp() is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. This function is for higher dimensional datasets that cannot be handled by a single core function RMSD() included in RMSD package. See Wada and Tsubaki (2013) <doi:10.1109/CLOUDCOM-ASIA.2013.86> for the detail of the algorithm.

This package provides functions to correct biased transition and fertility estimates in population projection matrices caused by small sample sizes. Small or short-term studies frequently produce structural zeros (biologically possible transitions never observed) and structural ones (transitions estimated at 100% survival, stasis, or mortality that are biologically implausible). Both distort matrix structure and bias estimates of population growth. Implements a multinomial-Dirichlet Bayesian prior for transition probabilities and a Gamma-Poisson prior for reproduction, allowing analysts to incorporate prior biological knowledge and regularise estimates from rare or unobserved events. Includes functions to compute marginal posterior credible intervals for all transition probabilities (transition_CrI()), visualise those intervals as point-range plots (plot_transition_CrI()), and display the full posterior beta density for each matrix entry (plot_transition_density()). Methods are described in Tremblay et al. (2021) <doi:10.1016/j.ecolmodel.2021.109526>.

Non-parametric clustering of joint pattern multi-genetic/epigenetic factors. This package contains functions designed to cluster subjects based on gene features including single nucleotide polymorphisms (SNPs), DNA methylation (CPG), gene expression (GE), and covariate data. The novel concept follows the general K-means (Hartigan and Wong (1979) <doi:10.2307/2346830> framework but uses weighted Euclidean distances across the gene features to cluster subjects. This approach is unique in that it attempts to capture all pairwise interactions in an effort to cluster based on their complex biological interactions.

Robust categorical data analysis based on the theory of C-estimation developed in Welz (2024) <doi:10.48550/arXiv.2403.11954>. For now, the package only implements robust estimation of polychoric correlation as proposed in Welz, Mair and Alfons (2026) <doi:10.1017/psy.2025.10066> and robust estimation of polyserial correlation (Welz, 2026 <doi:10.1017/psy.2026.10091>) with methods for printing and plotting. We will implement further models in future releases. In addition, the package is still experimental, so input arguments and class structure may change in future releases.

This package provides functions for implementing robust methods for functional linear regression. In the functional linear regression, we consider scalar-on-function linear regression and function-on-function linear regression.

Upload R data.frame to Arm Treasure Data, see <https://www.treasuredata.com/>. You can execute database or table handling for resources on Arm Treasure Data.

Rcmdr Plugin for the FactoMineR package.

Loads Axon Binary Files (both ABF and ABF2') created by Axon Instruments/Molecular Devices software such as pClamp'.

This package provides a suite of tools useful to read, visualize and export bivariate motion energy time-series. Lagged synchrony between subjects can be analyzed through windowed cross-correlation. Surrogate data generation allows an estimation of pseudosynchrony that helps to estimate the effect size of the observed synchronization. Kleinbub, J. R., & Ramseyer, F. T. (2020). rMEA: An R package to assess nonverbal synchronization in motion energy analysis time-series. Psychotherapy research, 1-14. <doi:10.1080/10503307.2020.1844334>.

Extracts tagged text from markdown manuscripts for inclusion in dynamically generated revision letters. Provides an R markdown template based on papaja::revision_letter_pdf() with comment cross-referencing, a system for managing multiple sections of extracted text, and a way to automatically determine the page number of quoted sections from PDF manuscripts.

This package provides functions for reading mass spectrometry data in mzXML format.

This package provides a set of tools to explore the behaviour statistics used for forensic DNA interpretation when close relatives are involved. The package also offers some useful tools for exploring other forensic DNA situations.

This package provides the robust gamma rank correlation coefficient as introduced by Bodenhofer, Krone, and Klawonn (2013) <DOI:10.1016/j.ins.2012.11.026> along with a permutation-based rank correlation test. The rank correlation coefficient and the test are explicitly designed for dealing with noisy numerical data.

Allows to limit the rate at which one or more functions can be called.

This package implements and enhances the estimation techniques described in Rousseeuw & Verboven (2002) <doi:10.1016/S0167-9473(02)00078-6> for the location and scale of very small samples.

Computes the ridge partial correlation coefficients in a high or ultra-high dimensional linear regression problem. An extended Bayesian information criterion is also implemented for variable selection. Users provide the matrix of covariates as a usual dense matrix or a sparse matrix stored in a compressed sparse column format. Detail of the method is given in the manual.

Collection of tools to calculate portfolio performance metrics. Portfolio performance is a key measure for investors. These metrics are important to analyse how effectively their money has been invested. This package uses portfolio theories to give investor tools to evaluate their portfolio performance. For more information see, Markowitz, H.M. (1952), <doi:10.2307/2975974>. Analysis of Investments & Management of Portfolios [2012, ISBN:978-8131518748].

Collection of portable choice dialog widgets.

This package provides a platform-independent browser-based interface for business analytics in R, based on the shiny package. The application combines the functionality of radiant.data', radiant.design', radiant.basics', radiant.model', and radiant.multivariate'.

This package provides two general frameworks to generate a multi-layer network. This also provides several methods to reveal the embedding of both nodes and layers. The reference paper can be found from the URL mentioned below. Ting Li, Zhongyuan Lyu, Chenyu Ren, Dong Xia (2023) <arXiv:2302.04437>.