This package includes functions to compute the area under the curve of selected measures: the area under the sensitivity curve (AUSEC), the area under the specificity curve (AUSPC), the area under the accuracy curve (AUACC), and the area under the receiver operating characteristic curve (AUROC). The curves can also be visualized. Support for partial areas is provided.

This package simplifies the creation of Excel .xlsx files by providing a high level interface to writing, styling and editing worksheets. Through the use of Rcpp, read/write times are comparable to the xlsx and XLConnect packages with the added benefit of removing the dependency on Java.

This package provides a solution for analyzing digital images of plankton. In combination with ImageJ, an image analysis system, it processes digital images, measures individuals, trains for automatic classification of taxa, and finally, measures plankton samples (abundances, total and partial size spectra or biomasses, etc.).

This package provides visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).

This package provides tools for the computation of the matrix exponential, logarithm, square root, and related quantities.

r-selectr translates a CSS3 selector into an equivalent XPath expression. This allows you to use CSS selectors when working with the XML package as it can only evaluate XPath expressions. Also provided are convenience functions useful for using CSS selectors on XML nodes. This package is a port of the Python package cssselect.

Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in http://doi.org/10.18637/jss.v045.i03. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.

The R package ggplot2 is a plotting system based on the grammar of graphics. GGally extends ggplot2 by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.

This package implements a self-organizing map which has application in gene clustering. It provides functions like:

• filtering data by certain floor, ceiling, max/min ratio, and max - min difference;

• normalization of the data;

• get the average distortion measure;

• train a self-organizing map;

• summarize a som object;

• yeast cell cycle.

This package aims to identify candidate genes that are differentially methylated between cases and controls. It applies Student's t-test and delta beta analysis to identify candidate genes containing multiple CpG sites.

This package provides a range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.

Content-preserving transformations transformations of PDF files such as split, combine, and compress. This package interfaces directly to the qpdf C++ API and does not require any command line utilities. Note that qpdf does not read actual content from PDF files: to extract text and data you need the pdftools package.

This is software accompanying the book 'Applied Smoothing Techniques for Data Analysis---The Kernel Approach with S-Plus Illustrations', Oxford University Press. It provides smoothing methods for nonparametric regression and density estimation

This package lets you construct paths to your project's files. Use the here function as a drop-in replacement for file.path, it will always locate the files relative to your project root.

This package implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.

This package provides a system for embedded scientific computing and reproducible research with R. The OpenCPU server exposes a simple but powerful HTTP API for RPC and data interchange with R. This provides a reliable and scalable foundation for statistical services or building R web applications. The OpenCPU server runs either as a single-user development server within the interactive R session, or as a multi-user stack based on Apache2.

The Tweedie compound Poisson distribution is a mixture of a degenerate distribution at the origin and a continuous distribution on the positive real line. It has been applied in a wide range of fields in which continuous data with exact zeros regularly arise. The cplm package provides likelihood based and Bayesian procedures for fitting common Tweedie compound Poisson linear models. In particular, models with hierarchical structures or extra zero inflation can be handled. Further, the package implements the Gini index based on an ordered version of the Lorenz curve as a robust model comparison tool involving zero-inflated and highly skewed distributions.

Query, set, and delete credentials from the git credential store. Manage GitHub tokens and other git credentials. This package is to be used by other packages that need to authenticate to GitHub and/or other git repositories.

This package provides a wrapper around the Parsing Expression Grammar Template Library, a C++11 library for generating parsing expression grammars, that makes it accessible within Rcpp. With this, developers can implement their own grammars and easily expose them in R packages.

This package provides a set of predicates and assertions for checking the properties of matrices. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This is a package for creating tiny yet beautiful documents and vignettes from R Markdown. The package provides the html_pretty output format as an alternative to the html_document and html_vignette engines that convert R Markdown into HTML pages. Various themes and syntax highlight styles are supported.

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

The encoding of color can be handled in many different ways, using different color spaces. As different color spaces have different uses, efficient conversion between these representations are important. This package provides a set of functions that gives access to very fast color space conversion and comparisons implemented in C++, and offers 100-fold speed improvements over the convertColor function in the grDevices package.

Flexibly restructure and aggregate data using just two functions: melt and cast. This package provides them.