This package contain data sets and utilities from Project MOSAIC used to teach mathematics, statistics, computation and modeling. Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.

This package enables the translation of ggplot2 graphs to an interactive web-based version and/or the creation of custom web-based visualizations directly from R. Once uploaded to a plotly account, plotly graphs (and the data behind them) can be viewed and modified in a web browser.

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

This package provides graphical scales that map data to aesthetics, and provides methods for automatically determining breaks and labels for axes and legends.

This package provides support for all calendars as specified in the Climate and Forecast (CF) Metadata Conventions for climate and forecasting data. The CF Metadata Conventions is widely used for distributing files with climate observations or projections, including the Coupled Model Intercomparison Project (CMIP) data used by climate change scientists and the Intergovernmental Panel on Climate Change (IPCC). This package specifically allows the user to work with any of the CF-compliant calendars (many of which are not compliant with POSIXt). The CF time coordinate is formally defined in the CF Metadata Conventions document.

This package contains utility functions used by the Genome Analysis Toolkit (GATK) to load tables and plot data. The GATK is a toolkit for variant discovery in high-throughput sequencing data.

This package provides model selection tools and selfStart functions to fit parametric curves in the nls, nlsList and nlme frameworks.

This package helps you create simple maps; add sub-plots like pie plots to a map or any other plot; format, plot and export gridded data. The package was developed for displaying fisheries data but most functions can be used for more generic data visualisation.

This package provides type-stable rolling window functions over any R data type. Cumulative and expanding windows are also supported. For more advanced usage, an index can be used as a secondary vector that defines how sliding windows are to be created.

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 implements an empirical Bayes approach for large-scale hypothesis testing and false discovery rate estimation.

The clusterCrit package provides an implementation of the following indices: Czekanowski-Dice, Folkes-Mallows, Hubert Γ, Jaccard, McNemar, Kulczynski, Phi, Rand, Rogers-Tanimoto, Russel-Rao or Sokal-Sneath. ClusterCrit defines several functions which compute internal quality indices or external comparison indices. The partitions are specified as an integer vector giving the index of the cluster each observation belongs to.

This package is a usability wrapper around snow for easier development of parallel R programs. This package offers e.g. extended error checks, and additional functions. All functions work in sequential mode, too, if no cluster is present or wished. The package is also designed as connector to the cluster management tool sfCluster, but can also used without it.

Compare complex R objects and reveal the key differences. This package was designed particularly for use in testing packages where being able to quickly isolate key differences makes understanding test failures much easier.

ICGE is a package that helps to estimate the number of real clusters in data as well as to identify atypical units. The underlying methods are based on distances rather than on unit x variables.

spacetime provides classes and methods for spatio-temporal data, including space-time regular lattices, sparse lattices, irregular data, and trajectories; utility functions for plotting data as map sequences (lattice or animation) or multiple time series; methods for spatial and temporal matching or aggregation, retrieving coordinates, print, summary, etc.

This package provides tools to estimate parameters of accumulated damage (load duration) models based on failure time data under a Bayesian framework, using Approximate Bayesian Computation (ABC), and to assess long-term reliability under stochastic load profiles.

This package provides an R interface to the C libstemmer library that implements Porter's word stemming algorithm for collapsing words to a common root to aid comparison of vocabulary. Currently supported languages are Danish, Dutch, English, Finnish, French, German, Hungarian, Italian, Norwegian, Portuguese, Romanian, Russian, Spanish, Swedish and Turkish.

This package provides an efficient interface to MPI by utilizing S4 classes and methods with a focus on Single Program/Multiple Data (SPMD) parallel programming style, which is intended for batch parallel execution.

This package provides tools to query and print information about the current R session. It is similar to utils::sessionInfo(), but includes more information about packages, and where they were installed from.

oai provides a general purpose client to work with any Open Archives Initiative Protocol for 'Metadata' Harvesting (OAI-PMH) service. Functions are provided to work with the OAI-PMH verbs: GetRecord, Identify, ListIdentifiers, ListMetadataFormats, ListRecords, and ListSets.

This package provides functions and datasets for the book "Modern Applied Statistics with S" (4th edition, 2002) by Venables and Ripley.

This package provides an mlr3 extension that provides various resampling-based confidence interval (CI) methods for estimating the generalization error. These CI methods are implemented as mlr3 measures, enabling the evaluation of individual algorithms on specific tasks as well as the comparison of different learning algorithms.

This is a C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data.