Generates pseudo-random vectors that follow an arbitrary von Mises-Fisher distribution on a sphere. This method is fast and efficient when generating a large number of pseudo-random vectors. Functions to generate random variates and compute density for the distribution of an inner product between von Mises-Fisher random vector and its mean direction are also provided. Details are in Kang and Oh (2024) <doi:10.1007/s11222-024-10419-3>.

ramr is an R package for detection of low-frequency aberrant methylation events in large data sets obtained by methylation profiling using array or high-throughput bisulfite sequencing. In addition, package provides functions to visualize found aberrantly methylated regions (AMRs), to generate sets of all possible regions to be used as reference sets for enrichment analysis, and to generate biologically relevant test data sets for performance evaluation of AMR/DMR search algorithms.

St implements a simple and lightweight terminal emulator. It implements 256 colors, most VT10X escape sequences, utf8, X11 copy/paste, antialiased fonts (using fontconfig), fallback fonts, resizing, and line drawing.

Estimate diagnosis performance (Sensitivity, Specificity, Positive predictive value, Negative predicted value) of a diagnostic test where can not measure the golden standard but can estimate it using the attributable fraction.

This package provides the source and examples for James P. Howard, II, "Computational Methods for Numerical Analysis with R," <https://jameshoward.us/cmna/>, a book on numerical methods in R.

This package performs least squares constrained optimization on a linear objective function. It contains a number of algorithms to choose from and offers a formula syntax similar to lm().

Bayesian networks with continuous and/or discrete variables can be learned and compared from data. The method is described in Boettcher and Dethlefsen (2003), <doi:10.18637/jss.v008.i20>.

Fit logistic functions to observed dose-response continuous data and evaluate goodness-of-fit measures. See Malyutina A., Tang J., and Pessia A. (2023) <doi:10.18637/jss.v106.i04>.

This package contains data sets, examples and software from the Second Edition of "Design of Observational Studies"; see Rosenbaum, P.R. (2010) <doi:10.1007/978-1-4419-1213-8>.

Statistical and graphical tools for detecting and measuring discrimination and bias, be it racial, gender, age or other. Detection and remediation of bias in machine learning algorithms. Python interfaces available.

Background correction of spectral like data. Handles variations in scaling, polynomial baselines, interferents, constituents and replicate variation. Parameters for corrections are stored for further analysis, and spectra are corrected accordingly.

This package provides tools for fluctuations analysis of mutant cells counts. Main reference is A. Mazoyer, R. Drouilhet, S. Despreaux and B. Ycart (2017) <doi:10.32614/RJ-2017-029>.

Routines for fitting various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations errors association, endogeneity, non-random sample selection or partial observability.

This package implements common geostatistical methods in a clean, straightforward, efficient manner. The methods are discussed in Schabenberger and Gotway (2004, <ISBN:9781584883227>) and Waller and Gotway (2004, <ISBN:9780471387718>).

This package implements assessment of benefit-risk balance using Bayesian Discrete Choice Experiment. For more details see the article by Mukhopadhyay et al. (2019) <DOI:10.1080/19466315.2018.1527248>.

This package provides a set of routines to quickly download and import the HGNC data set on mapping of gene symbols to gene entries in other popular databases or resources.

Smoothing techniques and computing bandwidth selectors of the nth derivative of a probability density for one-dimensional data (described in Arsalane Chouaib Guidoum (2020) <arXiv:2012.06102> [stat.CO]).

Analyzing data under multivariate mixed effects model using multivariate REML and multivariate Henderson3 methods. See Meyer (1985) <doi:10.2307/2530651> and Wesolowska Janczarek (1984) <doi:10.1002/bimj.4710260613>.

Generates multivariate subgaussian stable probabilities using the QRSVN algorithm as detailed in Genz and Bretz (2002) <DOI:10.1198/106186002394> but by sampling positive stable variates not chi/sqrt(nu).

An API package for the Members Name Information Service operated by the UK parliament. Documentation for the API itself can be found here: <http://data.parliament.uk/membersdataplatform/default.aspx>.

This package implements orbit counting using a fast combinatorial approach. Counts orbits of nodes and edges from edge matrix or data frame, or a graph object from the graph package.

Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).

This package provides functions to generate ensembles of generalized linear models using a greedy projected subset gradient descent algorithm. The sparsity and diversity tuning parameters are selected by cross-validation.

This function produces both the numerical and graphical summaries of the QTL hotspot detection in the genomes that are available on the worldwide web including the flanking markers of QTLs.