This package is an implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. It includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart).

This package provides a unified interface to interact with Docker and Singularity containers. You can execute a command inside a container, mount a volume or copy a file.

This package contains third-party map tile provider information from Leaflet.js, to be used with the leaflet R package. Additionally, leaflet.providers enables users to retrieve up-to-date provider information between package updates.

Designed for simplicity, a mirai evaluates an R expression asynchronously in a parallel process, locally or distributed over the network. The result is automatically available upon completion. Modern networking and concurrency, built on nanonext and NNG (Nanomsg Next Gen), ensures reliable and efficient scheduling over fast inter-process communications or TCP/IP secured by TLS. Distributed computing can launch remote resources via SSH or cluster managers. An inherently queued architecture handles many more tasks than available processes, and requires no storage on the file system. Innovative features include support for otherwise non-exportable reference objects, event-driven promises, and asynchronous parallel map.

This package provides binning and plotting functions for hexagonal bins. It uses and relies on grid graphics and formal (S4) classes and methods.

This package provides bitmapped vectors of booleans (no NAs), coercion from and to logicals, integers and integer subscripts, fast boolean operators and fast summary statistics. With bit class vectors of true binary booleans, TRUE and FALSE can be stored with 1 bit only.

This package contains functions for creating various types of summary tables, e.g. comparing characteristics across levels of a categorical variable and summarizing fitted generalized linear models, generalized estimating equations, and Cox proportional hazards models. Functions are available to handle data from simple random samples as well as complex surveys.

This package provides plotting functions for posterior analysis, model checking, and MCMC diagnostics. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling.

This package provides fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. It provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.

Streaming JSON (ndjson) has one JSON record per-line and many modern ndjson files contain large numbers of records. These constructs may not be columnar in nature, but it is often useful to read in these files and "flatten" the structure out to enable working with the data in an R data.frame-like context. Functions are provided that make it possible to read in plain ndjson files or compressed (gz) ndjson files and either validate the format of the records or create "flat" data.table structures from them.

This package provides a collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values.

This package supports arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental functions. To this end, the package interfaces with the Multiple Precision Floating-Point Reliable (MPFR) library.

This package implements the Subplex optimization algorithm. It solves unconstrained optimization problems using a simplex method on subspaces. The method is well suited for optimizing objective functions that are noisy or are discontinuous at the solution.

LIGER is a package for integrating and analyzing multiple single-cell datasets, developed and maintained by the Macosko lab. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors.

Convert a logical vector or a vector of p-values or a correlation, difference, or distance matrix into a display identifying the pairs for which the differences were not significantly different.

In putative Transcription Factor Binding Sites (TFBSs) identification from sequence/alignments, we are interested in the significance of certain match scores. TFMPvalue provides the accurate calculation of a p-value with a score threshold for position weight matrices, or the score with a given p-value. It is an interface to code originally made available by Helene Touzet and Jean-Stephane Varre, 2007, Algorithms Mol Biol:2, 15. Touzet and Varre (2007).

Create interactive 3D scatter plots, network plots, and globes in R using the three.js visualization library.

The package converts the input in any one of character, integer, numeric, factor, or an ordered type into POSIXct (or Date) objects, using one of a number of predefined formats, and relying on Boost facilities for date and time parsing.

This package provides basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002).

This package performs 2D Delaunay triangulation, constrained or unconstrained, with the help of the C++ library CDT. A function to plot the triangulation is provided. The constrained Delaunay triangulation has applications in geographic information systems.

This package provides a fast parallelized alternative to R's native dist function to calculate distance matrices for continuous, binary, and multi-dimensional input matrices, which supports a broad variety of predefined distance functions from other R packages, as well as user- defined functions written in C++. For ease of use, the parDist function extends the signature of the dist function and uses the same parameter naming conventions as distance methods of existing R packages.

This is a package supporting the analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.

This package extends the functionality of ggplot2, providing the capability to plot ternary diagrams for (a subset of) the ggplot2 geometries. Additionally, ggtern has implemented several new geometries which are unavailable to the standard ggplot2 release.

This package provides methods operating on rows and columns of matrices, e.g. rowMedians(), rowRanks(), and rowSds(). There are also some vector-based methods, e.g. binMeans(), madDiff() and weightedMedians(). All methods have been optimized for speed and memory usage.