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

This package provides a functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.

This package provides a collection of high-performance utilities. It can be used to compute distances, correlations, autocorrelations, clustering, and other tasks. It also contains a graph clustering algorithm described in MetaCell analysis of single-cell RNA-seq data using K-nn graph partitions.

This package provides a collection of dimensionality reduction techniques from R packages and provides a common interface for calling the methods.

Estimate quantile regression (QR) and composite quantile regression (cqr) and with adaptive lasso penalty using interior point (IP), majorize and minimize (MM), coordinate descent (CD), and alternating direction method of multipliers algorithms (ADMM).

The main purpose of this package is to provide the algorithmic complexity for short strings, an approximation of the Kolmogorov Complexity of a short string using the coding theorem method. While the database containing the complexity is provided in the data only package acss.data, this package provides functions accessing the data such as prob_random returning the posterior probability that a given string was produced by a random process. In addition, two traditional (but problematic) measures of complexity are also provided: entropy and change complexity.

This package lets you manage Google Drive files from R.

This package provides an R Shiny application to create visual abstracts for original research. A variety of user defined options and formatting are included.

Circle Manhattan Plot is an R package that can lay out genome-wide association study P-value results in both traditional rectangular patterns, QQ-plot and novel circular ones. United in only one bull's eye style plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals. Additional functions include: highlight signals, a group of SNPs, chromosome visualization and candidate genes around SNPs.

This package provides the Molecular Signatures Database (MSigDB) gene sets typically used with the Gene Set Enrichment Analysis (GSEA) software in a standard R data frame with key-value pairs. Included are the original human gene symbols and Entrez IDs as well as the equivalents for various frequently studied model organisms such as mouse, rat, pig, fly, and yeast.

This R package caches the results of a function so that when you call it again with the same arguments it returns the pre-computed value.

This is a package to simplify loading of system fonts and Google Fonts into R, in order to support other packages.

This package provides tools to read, write, create, and manipulate DESCRIPTION files. It is intended for packages that create or manipulate other packages.

Written in C++ using Rcpp, this package provides a collection of metrics for evaluating models.

The tkrplot package lets you place R graphics in a Tk, cross-platform graphical user interface toolkit widget.

This package processes accelerometer data from uni-axial and tri-axial devices and generates data summaries. Also, includes functions to plot, analyze, and simulate accelerometer data.

This package lets you manage configuration values across multiple environments (e.g. development, test, production). It reads values using a function that determines the current environment and returns the appropriate value.

This package provides a native R plotting library that provides a flexible declarative interface for creating interactive web-based graphics, backed by the Bokeh visualization library.

This package allows you to render vector-based SVG images into high-quality custom-size bitmap arrays using the librsvg2 library. The resulting bitmap can be written to e.g. PNG, JPEG or WEBP format. In addition, the package can convert images directly to various formats such as PDF or PostScript.

Analyze count time series with excess zeros. Two types of statistical models are supported: Markov regression and state-space models. They are also known as observation-driven and parameter-driven models respectively in the time series literature. The functions used for Markov regression or observation-driven models can also be used to fit ordinary regression models with independent data under the zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB) assumption. The package also contains miscellaneous functions to compute density, distribution, quantile, and generate random numbers from ZIP and ZINB distributions.

This package converts between R and Simple Feature sf objects, without depending on the Simple Feature library. Conversion functions are available at both the R level, and through Rcpp.

This package uses the node library is-my-json-valid or ajv to validate JSON against a JSON schema. Drafts 04, 06 and 07 of JSON schema are supported.

This package implements multitaper spectral estimation techniques using prolate spheroidal sequences (Slepians) and sine tapers for time series analysis. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates.

This package provides simulation methods for the evolution of antibody repertoires. The heavy and light chain variable region of both human and C57BL/6 mice can be simulated in a time-dependent fashion. Both single lineages using one set of V-, D-, and J-genes or full repertoires can be simulated. The algorithm begins with an initial V-D-J recombination event, starting the first phylogenetic tree. Upon completion, the main loop of the algorithm begins, with each iteration representing one simulated time step. Various mutation events are possible at each time step, contributing to a diverse final repertoire.