This package implements a self-sufficient reader and writer for flat Parquet files. It can read most Parquet data types. It can write many R data types, including factors and temporal types.

Parametric time warping aligns patterns. It aims to put corresponding features at the same locations. The algorithm searches for an optimal polynomial describing the warping. It is possible to align one sample to a reference, several samples to the same reference, or several samples to several references. One can choose between calculating individual warpings, or one global warping for a set of samples and one reference. Two optimization criteria are implemented: RMS error and WCC. Both warping of peak profiles and of peak lists are supported.

This package provides basic classes and methods for Natural Language Processing.

Constructs confidence intervals on the probability of success in a binomial experiment via several parameterizations

User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the StanHeaders package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.

This is a subset of the spatstat package, containing its functionality for spatial data on a linear network.

This package provides enhanced message functions (cat() / message() / warning() / error()) using wrappers around sprintf(). It also provides multiple assertion functions (e.g. to check class, length, values, files, arguments, etc.).

This package provides extended data frames, with a special data frame column which contains two indexes, with potentially a nesting structure.

This is a developer-focused, low dependency package in tidymodels that provides functions to register how models are to be used. Functions to register models are complimented with accessor functions to retrieve registered model information to aid in model fitting and error handling.

This package provides a collection of functions to support matrix calculations for probability, econometric and numerical analysis. There are additional functions that are comparable to APL functions which are useful for actuarial models such as pension mathematics.

This package provides an all relevant feature selection wrapper algorithm. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).

Regression methods to quantify the relation between two measurement methods are provided by this package. In particular it addresses regression problems with errors in both variables and without repeated measurements. It implements the CLSI recommendations (see J. A. Budd et al. (2018, https://clsi.org/standards/products/method-evaluation/documents/ep09/) for analytical method comparison and bias estimation using patient samples. Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators are implemented, see F. Dufey (2020, <doi:10.1515/ijb-2019-0157>) and J. Raymaekers and F. Dufey (2022, <arXiv:2202:08060>). A comprehensive overview over the implemented methods and references can be found in the manual pages mcr-package and mcreg.

This package provides useful functions to deal with the haven_labelled and haven_labelled_spss classes introduced by the haven package.

This package provides simple utility functions to read from and write to the system clipboards.

Many approaches for both reading and creating XML (and HTML) documents (including DTDs), both local and accessible via HTTP or FTP. Also offers access to an XPath "interpreter".

This package provides tools to create pretty tables for HTML documents and other formats. Functions are provided to let users create tables, modify and format their content. It extends the officer package and can be used within R markdown documents when rendering to HTML and to Word documents.

This package implements easy-to-use functions to generate 2-7 sets Venn plot in publication quality. ggVennDiagram plot Venn using well-defined geometry dataset and ggplot2. The shapes of 2-4 sets Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which are developed and imported from another package venn. We provide internal functions to integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections of them, then separately plot Venn in three components: set edges, set labels, and regions. From version 1.0, it is possible to customize these components as you demand in ordinary ggplot2 grammar.

This package provides wrappers on regexpr and gregexpr to return the match results in tidy data frames.

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

This package provides a ggplot2 extension for implementing parliament charts and several other useful visualizations.

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

Obtain any major version of jQuery and use it in any webpage generated by htmltools (e.g. shiny, htmlwidgets, and rmarkdown). Most R users don't need to use this package directly, but other R packages (e.g. shiny, rmarkdown, etc.) depend on this package to avoid bundling redundant copies of jQuery.

The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and isolate duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff.