This package defines sparse three-dimensional arrays and supports standard operations on them. The package also includes utility functions for matrix calculations that are common in statistics, such as quadratic forms.

This is a package for visualizing data quality of partially accruing data.

This package provides an interface for working with large matrices stored in files, not in computer memory. It supports multiple non-character data types (double, integer, logical and raw) of various sizes (e.g. 8 and 4 byte real values). Access to parts of the matrix is done by indexing, exactly as with usual R matrices. It supports very large matrices; the package has been tested on multi-terabyte matrices. It allows for more than 2^32 rows or columns, ad allows for quick addition of extra columns to a filematrix.

Bayesian density estimates for univariate continuous random samples are provided using the Bayesian inference engine paradigm. The engine options are: Hamiltonian Monte Carlo, the no U-turn sampler, semiparametric mean field variational Bayes and slice sampling. The methodology is described in Wand and Yu (2020), arXiv:2009.06182.

This package is meant to ease the creation of time-to-event (i.e. survival) endpoint figures. The modular functions create figures ready for publication. Each of the functions that add to or modify the figure are written as proper ggplot2 geoms or stat methods, allowing the functions from this package to be combined with any function or customization from ggplot2 and other ggplot2 extension packages.

This package carries out a mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB and polar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided.

This package provides functions and datasets from book Companion to Applied regression, Second Edition, Sage, 2011.

This package implements asymptotic methods related to maximally selected statistics, with applications to single-nucleotide polymorphism (SNP) data.

This package provides a mutation analysis tool that discovers cancer driver genes with frequent mutations in protein signalling sites such as post-translational modifications (phosphorylation, ubiquitination, etc). The Poisson generalized linear regression model identifies genes where cancer mutations in signalling sites are more frequent than expected from the sequence of the entire gene. Integration of mutations with signalling information helps find new driver genes and propose candidate mechanisms to known drivers.

This package provides functions for testing affine hypotheses on the regression coefficient vector in regression models with autocorrelated errors.

This is a package for visualizing functional data and identifying functional outliers with bagplots, boxplots and rainbow plots.

This package provides an interface to Amazon Web Services customer engagement services, including Simple Email Service, Connect contact center service, and more.

This package provides data sets from project Mosaic http://mosaic-web.org used to teach mathematics, statistics, computation and modeling.

This package provides fast and memory efficient methods for truncated singular and eigenvalue decompositions, as well as for principal component analysis of large sparse or dense matrices.

Functions and examples are provided for transmission/disequilibrium tests for extended marker haplotypes, as in Clayton, D. and Jones, H. (1999) "Transmission/disequilibrium tests for extended marker haplotypes".

This package provides functions to extract commonly used fragmentation metrics to quantify time accumulation strategies based on minute level actigraphy-measured activity counts data.

This package provides some easy-to-use functions to extract and visualize the output of multivariate data analyses, including PCA (Principal Component Analysis), CA (Correspondence Analysis), MCA (Multiple Correspondence Analysis), FAMD (Factor Analysis of Mixed Data), MFA (Multiple Factor Analysis) and HMFA (Hierarchical Multiple Factor Analysis) functions from different R packages. It contains also functions for simplifying some clustering analysis steps and provides ggplot2-based elegant data visualization.

This package provides support for the foreach looping construct. foreach is an idiom that allows for iterating over elements in a collection, without the use of an explicit loop counter. This package in particular is intended to be used for its return value, rather than for its side effects. In that sense, it is similar to the standard lapply function, but doesn't require the evaluation of a function. Using foreach without side effects also facilitates executing the loop in parallel.

This package performs augmented backward elimination and checks the stability of the obtained model. Augmented backward elimination combines significance or information based criteria with the change in estimate to either select the optimal model for prediction purposes or to serve as a tool to obtain a practically sound, highly interpretable model.

This is a package for estimation of one-dimensional probability distributions including kernel density estimation, weighted empirical cumulative distribution functions, Kaplan-Meier and reduced-sample estimators for right-censored data, heat kernels, kernel properties, quantiles and integration.

This package extends shinydashboard with AdminLTE2 components. AdminLTE2 is a Bootstrap 3 dashboard template. Customize boxes, add timelines and a lot more.

This package provides a collection of R functions for analyzing finite mixture models.

This package provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling.

This package provides a collection of libraries for numerical computing (numerical integration, optimization, etc.) and their integration with Rcpp.