This package generates version 2 and 4 request signatures for Amazon Web Services (AWS) and provides a mechanism for retrieving credentials from environment variables, AWS credentials files, and EC2 instance metadata. For use on EC2 instances, the package 'aws.ec2metadata' is suggested.

This package infers directional Conservative causal core (gene) networks (C3NET). This is a version of the algorithm C3NET with directional network.

This package provides an R interface to functions of the SAMtools library.

Tree based algorithms can be improved by introducing boosting frameworks. LightGBM is one such framework, based on Ke, Guolin et al. (2017). This package offers an R interface to work with it. It is designed to be distributed and efficient with the following goals:

1. Faster training speed and higher efficiency;

2. lower memory usage;

3. better accuracy;

4. parallel learning supported; and

5. capable of handling large-scale data.

Many approaches for both reading and creating XML (and HTML) documents (including DTDs), both local and accessible via HTTP or FTP. Also offers access to an XPath "interpreter".

This package provides functions for applying a wide range of fisheries stock assessment methods.

Call job::job(<code here>) to run R code as an RStudio job and keep your console free in the meantime. This allows for a productive workflow while testing (multiple) long-running chunks of code. It can also be used to organize results using the RStudio Jobs GUI or to test code in a clean environment. Two RStudio Addins can be used to run selected code as a job.

Obtain any major version of jQuery and use it in any webpage generated by htmltools (e.g. shiny, htmlwidgets, and rmarkdown). Most R users don't need to use this package directly, but other R packages (e.g. shiny, rmarkdown, etc.) depend on this package to avoid bundling redundant copies of jQuery.

This package provides an R wrapper for the special functions and quasi random number generators of the GNU Scientific Library.

The ggplot2 package provides a strong API for sequentially building up a plot, but does not concern itself with composition of multiple plots. Patchwork is a package that expands the API to allow for arbitrarily complex composition of plots by providing mathematical operators for combining multiple plots.

This package provides implementations of apply(), eapply(), lapply(), Map(), mapply(), replicate(), sapply(), tapply(), and vapply() that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster.

This package implements S4 classes and various tools for financial time series. Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions are provided.

This package provides a statistical method to impute the missing values in accelerometer data. The methodology includes both parametric and semi-parametric multiple imputations under the zero-inflated Poisson lognormal model. It also provides multiple functions to preprocess the accelerometer data previous to the missing data imputation. These include detecting the wearing and the non-wearing time, selecting valid days and subjects, and creating plots.

This package contains the Rook specification and convenience software for building and running Rook applications. A Rook application is an R reference class object that implements a call method or an R closure that takes exactly one argument, an environment, and returns a list with three named elements: the status, the headers, and the body.

This package provides procedures for fitting a principal curve to a data matrix in arbitrary dimensions.

The lpSolveAPI package provides an R interface to lp_solve, a MILP, solver with support for pure linear, (mixed) integer/binary, semi-continuous and SOS models.

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.

This package provides tools to perform analyses and combine results from multiple-imputation datasets.

This package implements data manipulation methods such as cast, aggregate, and merge/join for Matrix and Matrix-like objects.

This package provides a convenience wrapper that uses the rmarkdown package to render small snippets of code to target formats that include both code and output. The goal is to encourage the sharing of small, reproducible, and runnable examples on code-oriented websites or email. reprex also extracts clean, runnable R code from various common formats, such as copy/paste from an R session.

This package provides various R programming tools for model fitting.

This package provides tools to generate a violin point plot, a combination of a violin/histogram plot and a scatter plot by offsetting points within a category based on their density using quasirandom noise.

This package provides tools to calculate exact and approximate theory experimental designs for D, A, and I criteria. Very large designs may be created. Experimental designs may be blocked or blocked designs created from a candidate list, using several criteria. The blocking can be done when whole and within plot factors interact.

This package provides data structures and basic operations for ordinary sets, generalizations such as fuzzy sets, multisets, and fuzzy multisets, customizable sets, and intervals.