Rcpp access to the CCTZ timezone library is provided. CCTZ is a C++ library for translating between absolute and civil times using the rules of a time zone. The CCTZ source code is included in this package.

Tidyft is an extension of data.table. It uses modifification by reference whenever possible. This toolkit is designed for big data analysis in high-performance desktop or laptop computers. The syntax of the package is similar or identical to tidyverse.

This package provides tools for accessing the Botanical Information and Ecology Network (BIEN) database. The BIEN database contains cleaned and standardized botanical data including occurrence, trait, plot and taxonomic data. This package provides functions that query the BIEN database by constructing and executing optimized SQL queries.

This package provides new statistics, new geometries and new positions for ggplot2 and a suite of functions to facilitate the creation of statistical plots.

This package provides classes and methods for spatial data; the classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc.

Phylogenetic trees generally contain multiple components including nodes, edges, branches and associated data. This package provides an approach to convert tree objects to tidy data frames. It also provides tidy interfaces to manipulate tree data.

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 provides tools to fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic tree.

This package provides various methods for MRI tissue classification.

This package combines a forecast of a time series, using the function forecast, with the dynamic plots from dygraphs.

This package provides functions for easily manipulating colors, creating color scales and calculating color distances.

This package provides datasets associated with the gap package. Currently, it includes an example data for regional association plot (CDKN), an example data for a genomewide association meta-analysis (OPG), data in studies of Parkinson's diease (PD), ALHD2 markers and alcoholism (aldh2), APOE/APOC1 markers and Schizophrenia (apoeapoc), cystic fibrosis (cf), a Olink/INF panel (inf1), Manhattan plots with (hr1420, mhtdata) and without (w4) gene annotations.

This package provides various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps.

This package provides bindings to libsodium: a library for encryption, decryption, signatures, password hashing and more. Sodium uses curve25519, a Diffie-Hellman function by Daniel Bernstein, which has become very popular after it was discovered that the NSA had backdoored Dual EC DRBG.

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 provides functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing".

This package provides routines for the statistical analysis of landmark shapes, including Procrustes analysis, graphical displays, principal components analysis, permutation and bootstrap tests, thin-plate spline transformation grids and comparing covariance matrices. See Dryden, I.L. and Mardia, K.V. (2016). Statistical shape analysis, with Applications in R (2nd Edition), John Wiley and Sons.

This package extends the fitdistr function of the MASS package with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left-censored, right-censored and interval-censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME) and maximum goodness-of-fit estimation (MGE) methods (available only for non-censored data). Weighted versions of MLE, MME and QME are available.

This package provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline.

This package provides tools to estimate tail area-based false discovery rates as well as local false discovery rates for a variety of null models (p-values, z-scores, correlation coefficients, t-scores). The proportion of null values and the parameters of the null distribution are adaptively estimated from the data. In addition, the package contains functions for non-parametric density estimation (Grenander estimator), for monotone regression (isotonic regression and antitonic regression with weights), for computing the greatest convex minorant (GCM) and the least concave majorant (LCM), for the half-normal and correlation distributions, and for computing empirical higher criticism (HC) scores and the corresponding decision threshold.

Data exploration and modelling is a process in which a lot of data artifacts are produced. Artifacts like: subsets, data aggregates, plots, statistical models, different versions of data sets and different versions of results. Archivist helps to store and manage artifacts created in R. It allows you to store selected artifacts as binary files together with their metadata and relations. Archivist allows sharing artifacts with others. It can look for already created artifacts by using its class, name, date of the creation or other properties. It also makes it easy to restore such artifacts.

This package provides the datasets to support the Fish Stock Assessment (FSA) package.

This package provides a set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape. The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a log or a logit transformation, respectively.

Changepoint implements various mainstream and specialised changepoint methods. These methods are suitable for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included as well.