The DHARMa package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as JAGS, STAN, or BUGS can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial, phylogenetic and temporal autocorrelation.

This package serves two purposes:

1. Provide a comfortable R interface to query the Google server for static maps, and

2. Use the map as a background image to overlay plots within R. This requires proper coordinate scaling.

This package contains routines for logspline density estimation. The function oldlogspline() uses the same algorithm as the logspline package version 1.0.x; i.e., the Kooperberg and Stone (1992) algorithm (with an improved interface). The recommended routine logspline() uses an algorithm from Stone et al (1997).

This package provides a collection of meta-analysis datasets for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.

This package implements the R version of the log4j package. It offers hierarchic loggers, multiple handlers per logger, level based filtering, space handling in messages and custom formatting.

This package lets you read and write JSON Web Keys (JWK, rfc7517), generate and verify JSON Web Signatures (JWS, rfc7515) and encode/decode JSON Web Tokens (JWT, rfc7519). These standards provide modern signing and encryption formats that are natively supported by browsers via the JavaScript WebCryptoAPI, and used by services like OAuth 2.0, LetsEncrypt, and Github Apps.

This package is a compatibility wrapper to replace the orphaned package by Romain Francois. New applications should use the openssl or base64enc package instead.

This package provides functions for obtaining the density, random variates and maximum likelihood estimates of the Zero-truncated Poisson lognormal distribution and their mixture distribution.

This package provides an implementation of heatmaps that offers more control over dimensions and appearance.

This package contains procedures for depth-based supervised learning, which are entirely non-parametric, in particular the DDalpha-procedure (Lange, Mosler and Mozharovskyi, 2014). The training data sample is transformed by a statistical depth function to a compact low-dimensional space, where the final classification is done. It also offers an extension to functional data and routines for calculating certain notions of statistical depth functions. 50 multivariate and 5 functional classification problems are included.

This package provides a graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering. In addition, corrplot is good at details, including choosing color, text labels, color labels, layout, etc.

Iterated race is an extension of the Iterated F-race method for the automatic configuration of optimization algorithms, that is, (offline) tuning their parameters by finding the most appropriate settings given a set of instances of an optimization problem.

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.

This package provides a close to zero dependency package to draw and display Venn diagrams up to 7 sets, and any Boolean union of set intersections.

This package provides a derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M. J. D. Powell.

This package provides an interface to Amazon Web Services networking and content delivery services, including Route 53 Domain Name System service, CloudFront content delivery, load balancing, and more.

This package provides a collection of functions that perform operations on time-series accelerometer data, such as identify the non-wear time, flag minutes that are part of an activity bout, and find the maximum 10-minute average count value. The functions are generally very flexible, allowing for a variety of algorithms to be implemented.

This is a deprecated package for calculating pairwise multiple comparisons of mean rank sums. This package is superseded by the novel PMCMRplus package. The PMCMR package is no longer maintained, but kept for compatibility of dependent packages for some time.

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 provides the dyn class interfaces ts, irts, zoo and zooreg time series classes to lm, glm, loess, quantreg::rq, MASS::rlm, MCMCpack::MCMCregress(), quantreg::rq(), randomForest::randomForest() and other regression functions, allowing those functions to be used with time series including specifications that may contain lags, diffs and missing values.

This light-weight package helps you track and visualize the progress of parallel versions of vectorized R functions of the mc*apply family.

The r-abhgenotyper package provides simple imputation, error-correction and plotting capacities for genotype data. The package is supposed to serve as an intermediate but independent analysis tool between the TASSEL GBS pipeline and the r-qtl package. It provides functionalities not found in either TASSEL or r-qtl in addition to visualization of genotypes as "graphical genotypes".

This package contains data structures and algorithms for sparse arrays and matrices, based on index arrays and simple triplet representations, respectively.

This package provides tools for shrunken centroids regularized discriminant analysis for the purpose of classifying high dimensional data.