This package provides statistical models of biased sampling in the form of univariate and multivariate noncentral hypergeometric distributions, including Wallenius' noncentral hypergeometric distribution and Fisher's noncentral hypergeometric distribution (also called extended hypergeometric distribution).

This package provides pure R tools to read BMP format images. It is currently limited to 8 bit greyscale images and 24, 32 bit (A)RGB images.

This package provides a header-only C++ library is provided with support for dates, time zones, ISO weeks, Julian dates, and Islamic dates. date offers extensive date and time functionality for the C++11, C++14 and C++17 standards. A slightly modified version has been accepted (along with tz.h) as part of C++20. This package regroups all header files from the upstream repository so that other R packages can use them in their C++ code.

r-rvest helps you scrape information from web pages. It is designed to work with magrittr to make it easy to express common web scraping tasks, inspired by libraries like BeautifulSoup.

This package provides procedures for fitting a principal curve to a data matrix in arbitrary dimensions.

This package provides a collection of functions useful in learning and practicing Item Response Theory (IRT), which can be combined into larger programs. It provides basic CTT analysis, a simple common interface to the estimation of item parameters in IRT models for binary responses with three different programs (ICL, BILOG-MG, and ltm), ability estimation (MLE, BME, EAP, WLE, plausible values), item and person fit statistics, scaling methods (MM, MS, Stocking-Lord, and the complete Hebaera method), and a rich array of parametric and non-parametric (kernel) plots. It estimates and plots Haberman's interaction model when all items are dichotomously scored.

mlr3misc provides frequently used helper functions and assertions used in mlr3 and its companion packages. It comes with helper functions for functional programming, for printing, to work with data.table, as well as some generally useful R6 classes. This package also supersedes the package BBmisc.

This package provides tools to compute marginal effects from statistical models and return the result as tidy data frames. These data frames are ready to use with the ggplot2 package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The two main functions are ggpredict() and ggeffect(). There is a generic plot() method to plot the results using ggplot2.

This is a package for reading, manipulating, writing and plotting spatiotemporal arrays (raster and vector data cubes) in R, using GDAL bindings provided by sf, and NetCDF bindings by ncmeta and RNetCDF.

The Rsolnp package implements a general non-linear augmented Lagrange multiplier method solver, a sequential quadratic programming (SQP) based solver).

This R package provides a suite of tools to evaluate clustering algorithms, clusterings, and individual clusters.

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 provides a flexible approach to Bayesian optimization / model based optimization building on the bbotk package. The mlr3mbo is a toolbox providing both ready-to-use optimization algorithms as well as their fundamental building blocks allowing for straightforward implementation of custom algorithms. Single- and multi-objective optimization is supported as well as mixed continuous, categorical and conditional search spaces. Moreover, using mlr3mbo for hyperparameter optimization of machine learning models within the mlr3 ecosystem is straightforward via mlr3tuning.

Circle Manhattan Plot is an R package that can lay out genome-wide association study P-value results in both traditional rectangular patterns, QQ-plot and novel circular ones. United in only one bull's eye style plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals. Additional functions include: highlight signals, a group of SNPs, chromosome visualization and candidate genes around SNPs.

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 performs approximate bayesian computation (ABC) model choice and parameter inference via random forests. This machine learning tool named random forests (RF) can conduct selection among the highly complex models covered by ABC algorithms.

The sqldf function is typically passed a single argument which is an SQL select statement where the table names are ordinary R data frame names. sqldf transparently sets up a database, imports the data frames into that database, performs the SQL statement and returns the result using a heuristic to determine which class to assign to each column of the returned data frame. The sqldf or read.csv.sql functions can also be used to read filtered files into R even if the original files are larger than R itself can handle.

This package contains methods for the detection of clusters in hierarchical clustering dendrograms.

This package provides a Davidian curve defines a seminonparametric density, whose shape and flexibility can be tuned by easy to estimate parameters. Since a special case of a Davidian curve is the standard normal density, Davidian curves can be used for relaxing normality assumption in statistical applications (Zhang & Davidian, 2001) <doi:10.1111/j.0006-341X.2001.00795.x>. This package provides the density function, the gradient of the loglikelihood and a random generator for Davidian curves.

This package allows for fast, correct, consistent, portable, as well as convenient character string/text processing in every locale and any native encoding. Owing to the use of the ICU library, the package provides R users with platform-independent functions known to Java, Perl, Python, PHP, and Ruby programmers. Among available features there are: pattern searching (e.g. via regular expressions), random string generation, string collation, transliteration, concatenation, date-time formatting and parsing, etc.

This package provides a common interface to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. R, Spark, Stan, etc).

This package provides methods for manipulating regression models and for describing these in a style adapted for medical journals. It contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots. In addition to the descriptive methods, there are functions for the robust covariance matrix provided by the sandwich package, a function for adding non-linearities to a model, and a wrapper around the Epi package's Lexis() functions for time-splitting a dataset when modeling non-proportional hazards in Cox regressions.

This package contains various routines for drawing ellipses and ellipse-like confidence regions, implementing the plots described in Murdoch and Chow (1996), A graphical display of large correlation matrices, The American Statistician 50, 178-180. There are also routines implementing the profile plots described in Bates and Watts (1988), Nonlinear Regression Analysis and its Applications.

This package provides bindings to ImageMagick, a comprehensive image processing library. It supports many common formats (PNG, JPEG, TIFF, PDF, etc.) and manipulations (rotate, scale, crop, trim, flip, blur, etc). All operations are vectorized via the Magick++ STL meaning they operate either on a single frame or a series of frames for working with layers, collages, or animation. In RStudio, images are automatically previewed when printed to the console, resulting in an interactive editing environment.