Carries out integrative clustering analysis using multiple types of genomic dataset using integrative Non-negative Matrix factorization.

Locally sparse estimator of generalized varying coefficient model for asynchronous longitudinal data by kernel-weighted estimating equation.

Multivariate ARIMA and ARIMA-X estimation using Spliid's algorithm (marima()) and simulation (marima.sim()).

Combination of either p-values or modified effect sizes from different studies to find differentially expressed genes.

Collection of functions to perform fixed and random-effects multivariate and univariate meta-analysis and meta-regression.

Retrieve and plot word frequencies through time from the "Google Ngram Viewer" <https://books.google.com/ngrams>.

This package provides functions and data sets for the text Probability and Statistics with R, Second Edition.

Streamlines geographic data transformation, storage and publication, simplifying data preparation and enhancing interoperability across formats and platforms.

Allow sharing sensitive information, for example passwords, API keys, etc., in R packages, using public key cryptography.

Providing just one primary function, readit uses a set of reasonable heuristics to apply the appropriate reader function to the given file path. As long as the data file has an extension, and the data is (or can be coerced to be) rectangular, readit() can probably read it.

The handling of an API key (misnomer for password) for protected data can be difficult. This package provides secure convenience functions for entering / handling API keys and pulling data directly into memory. By default it will load from REDCap instances, but other sources are injectable via inversion of control.

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.

R implementation of Maximum Likelihood Principal Component Analysis The main idea of this package is to have an alternative way of PCA for subspace modeling that considers measurement errors. More details can be found in Peter D. Wentzell (2009) <doi:10.1016/B978-0-444-64165-6.03029-9>.

This package computes model and semi partial R squared with confidence limits for the linear and generalized linear mixed model (LMM and GLMM). The R squared measure from L. J. Edwards et al. (2008) is extended to the GLMM using penalized quasi-likelihood (PQL) estimation (see Jaeger et al. (2016)).

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 is a companion package of the book "R Programming: Zero to Pro" <https://r02pro.github.io/>. It contains the datasets used in the book and provides interactive exercises corresponding to the book. It covers a wide range of topics including visualization, data transformation, tidying data, data input and output.

In order to facilitate parsing of http requests and creating appropriate responses this package provides two classes to handle a lot of the housekeeping involved in working with http exchanges. The infrastructure builds upon the rook specification and is thus well suited to be combined with httpuv based web servers.

BaseX <https://basex.org> is a XML database engine and a compliant XQuery 3.1 processor with full support of W3C Update Facility'. This package is a full client-implementation of the client/server protocol for BaseX and provides functionalities to create, manipulate and query on XML-data.

This package provides an object for plotting GRanges, RleList, UCSC file formats, and ffTrack objects in multi-track panels.

The gg.gap function enables you to define segments for the y-axis in a ggplot2 plot.

This package provides classes and methods for dense and sparse matrices and operations on them using LAPACK and SuiteSparse.

Computes local polynomial estimators for the regression and also density. It comprises several different utilities to handle kernel estimators.

This package lets you convert R Markdown documents and Jupyter notebooks to a variety of output formats using Quarto.

Rove is a unit testing framework for Common Lisp applications. This is intended to be a successor of Prove.