This package allows users to test characteristics of common R objects.

This package provides tools for the analysis of high-dimensional data developed/implemented at the group "Statistical Complexity Reduction In Molecular Epidemiology" (SCRIME). The main focus is on SNP data, but most of the functions can also be applied to other types of categorical data.

This package provides the functionality to set configuration options on a per-package basis. Options set by a given package only apply to that package, other packages are unaffected.

This package provides tools to infer the code style (which style rules are followed and which ones are not) from one package and use it to check another. This makes it easier to find and correct the most important problems first.

This package lets you import OpenDocument Spreadsheet (ODS) into R as a data frame. It also supports writing data frames to an ODS file.

Similarly to Schafer's package pan, jomo is a package for multilevel joint modelling multiple imputation http://doi.org/10.1002/9781119942283. Novel aspects of jomo are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.

This package provides streamlined data import and export infrastructure by making assumptions that the user is probably willing to make: import and export determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., stringsAsFactors=FALSE), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, convert, provides a simple method for converting between file types.

This R package provides access to the code and data sets published by the statistics blog FiveThirtyEight.

Manage the life cycle of your exported functions with shared conventions, documentation badges, and non-invasive deprecation warnings. The lifecycle package defines four development stages (experimental, maturing, stable, and questioning) and three deprecation stages (soft-deprecated, deprecated, and defunct). It makes it easy to insert badges corresponding to these stages in your documentation. Usage of deprecated functions are signalled with increasing levels of non-invasive verbosity.

This package implements the Differential Evolution algorithm. This algorithm is used for the global optimization of a real-valued function of a real-valued parameter vector. The implementation of DifferentialEvolution in DEoptim interfaces with C code for efficiency.

This is a supplement to the maps package providing the larger and/or higher-resolution databases.

This package provides computationally efficient tools related to the multivariate normal and Student's t distributions. The main functionalities are: simulating multivariate random vectors, evaluating multivariate normal or Student's t densities and Mahalanobis distances. These tools are developed using C++ code and of the OpenMP API.

This package provides extensions to ggplot2, respecting the grammar of its graphics paradigm.

This package facilitates mapping by making natural earth map data from https://www.naturalearthdata.com/ more easily available to R users.

This package allows you to render vector-based SVG images into high-quality custom-size bitmap arrays using the librsvg2 library. The resulting bitmap can be written to e.g. PNG, JPEG or WEBP format. In addition, the package can convert images directly to various formats such as PDF or PostScript.

This is a package supporting the analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.

This package creates and manages simple key-value stores. These can use a variety of approaches for storing the data. This package implements the base methods and support for file system, in-memory and DBI-based database stores.

This package provides authentication helpers for Snowflake. It provides compatibility with authentication approaches supported by the Snowflake Connector for Python and the Snowflake CLI.

This package provides a collection of helper functions designed to help you to better understand object oriented programming in R, particularly using S3.

Logging functions in RcppSpdlog provide access to the logging functionality from the spdlog C++ library. This package offers shorter convenience wrappers for the R functions which match the C++ functions, namely via, say, spdl::debug() at the debug level. The actual formatting is done by the fmt::format() function from the fmtlib library (that is also std::format() in C++20 or later).

This package provides a collection of dimensionality reduction techniques from R packages and provides a common interface for calling the methods.

This package provides an implementation of the Tukey, Mandel, Johnson-Graybill, LBI, Tusell and modified Tukey non-additivity tests.

When analyzing data, plots are a helpful tool for visualizing data and interpreting statistical models. This package provides a set of simple tools for building plots incrementally, starting with an empty plot region, and adding bars, data points, regression lines, error bars, gradient legends, density distributions in the margins, and even pictures. The package builds further on R graphics by simply combining functions and settings in order to reduce the amount of code to produce for the user. As a result, the package does not use formula input or special syntax, but can be used in combination with default R plot functions.

This package provides auxiliary functions and data sets for "Ecological Models and Data", a book presenting maximum likelihood estimation and related topics for ecologists (ISBN 978-0-691-12522-0).