Uniform manifold approximation and projection is a technique for dimension reduction. This package provides an interface to the UMAP algorithm in R, including a translation of the original algorithm into R.

This package contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX code, and recoding variables.

This package lets you download Google fonts and generate CSS to use in rmarkdown documents and Shiny applications. Some popular fonts are included and ready to use.

This package provides a ggplot2 extension that enables the rendering of complex formatted plot labels (titles, subtitles, facet labels, axis labels, etc.). Text boxes with automatic word wrap are also supported.

Set of tools for reading and processing spatial data. The aim is to supply the workflow to create thematic maps. This package also facilitates tmap, the package for visualizing thematic maps.

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 a simple and flexible way to generate Circos 2D track plot images. The types of plots include: heatmap, histogram, lines, scatterplot, tiles and plot items for further decorations include connector, link (lines and ribbons), and text (gene) label. All functions require only R graphics packages that comes with the base installation.

Structural equation modeling (SEM) has a long history of representing models graphically as path diagrams. The semPlot package for R fills the gap between advanced, but time-consuming, graphical software and the limited graphics produced automatically by SEM software. In addition, semPlot offers more functionality than drawing path diagrams: it can act as a common ground for importing SEM results into R. Any result usable as input to semPlot can also be represented in any of the three popular SEM frame-works, as well as translated to input syntax for the R packages sem and lavaan.

The nls.lm function provides an R interface to lmder and lmdif from the MINPACK library, for solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support for lower and upper parameter bounds. The implementation can be used via nls-like calls using the nlsLM function.

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

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 functions for the hyperbolic and related distributions. Density, distribution and quantile functions and random number generation are provided for the hyperbolic distribution, the generalized hyperbolic distribution, the generalized inverse Gaussian distribution and the skew-Laplace distribution. Additional functionality is provided for the hyperbolic distribution, normal inverse Gaussian distribution and generalized inverse Gaussian distribution, including fitting of these distributions to data. Linear models with hyperbolic errors may be fitted using hyperblmFit.

How fast can you type R functions on your keyboard? Find out by running a zty.pe game: export R functions as instructions to type to destroy opponents' vessels.

Subject recruitment for medical research is challenging. Slow patient accrual leads to delay in research. Accrual monitoring during the process of recruitment is critical. Researchers need reliable tools to manage the accrual rate. This package provides an implementation of a Bayesian method that integrates researcher's experience on previous trials and data from the current study, providing reliable prediction on accrual rate for clinical studies. It provides functions for Bayesian accrual prediction which can be easily used by statisticians and clinical researchers.

mlr3learners extends mlr3 and mlr3proba with interfaces to essential machine learning packages on CRAN. This includes, but is not limited to: (penalized) linear and logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, naive Bayes, support vector machines, and gradient boosting.

The goal of this package is to generate an attractive and useful website from a source package. pkgdown converts your documentation, vignettes, README file, and more to HTML making it easy to share information about your package online.

Inspired by the the futile.logger R package and logging Python module, this utility provides a flexible and extensible way of formatting and delivering log messages with low overhead.

This package computes Hartigan's dip test statistic for unimodality, multimodality and provides a test with simulation based p-values, where the original public code has been corrected.

The objective of this package is to perform inference using an expressive statistical grammar that coheres with the Tidy design framework.

This package provides fundamental physical constants (quantity, value, uncertainty, unit) for SI and non-SI units, plus unit conversions based on the data from NIST, USA.

This package provides the "enrich" method to enrich list-like R objects with new, relevant components. The current version has methods for enriching objects of class family, link-glm, lm, glm and betareg. The resulting objects preserve their class, so all methods associated with them still apply. The package also provides the enriched_glm function that has the same interface as glm but results in objects of class enriched_glm. In addition to the usual components in a glm object, enriched_glm objects carry an object-specific simulate method and functions to compute the scores, the observed and expected information matrix, the first-order bias, as well as model densities, probabilities, and quantiles at arbitrary parameter values. The package can also be used to produce customizable source code templates for the structured implementation of methods to compute new components and enrich arbitrary objects.

This package provides RStudio addins and R functions that make copy-pasting vectors and tables to text painless.

It is sometimes useful to perform a computation in a separate R process, without affecting the current R process at all. This package does exactly that.

The main aim of the pander R package is to provide a minimal and easy tool for rendering R objects into Pandoc's markdown. The package is also capable of exporting/converting complex Pandoc documents (reports) in various ways.