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This package provides utilities for computing measures to assess model quality, which are not directly provided by R's base or stats packages. These include e.g. measures like r-squared, intraclass correlation coefficient, root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models.
This package provides tools to combine multidimensional arrays into a single array. This is a generalization of cbind and rbind. It works with vectors, matrices, and higher-dimensional arrays. It also provides the functions adrop, asub, and afill for manipulating, extracting and replacing data in arrays.
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 contains an efficient implementation of Sen's slope method (Sen, 1968) plus implementation of Xuebin Zhang's (Zhang, 1999) and Yue-Pilon's (Yue, 2002) pre-whitening approaches to determining trends in climate data.
XML-RPC is a remote procedure call protocol based on XML. The xmlrpc2 package is inspired by the XMLRPC package but uses the curl and xml2 packages instead of RCurl and XML'.
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.
Functions to help implement the extraction / subsetting / indexing function [ and replacement function [<- of custom matrix-like types (based on S3, S4, etc.), modeled as closely to the base matrix class as possible (with tests to prove it).
This package includes HTML functions and methods to write in an HTML file. Thus, making HTML reports is easy. It includes a function that allows redirection on the fly, which appears to be very useful for teaching purposes, as the student can keep a copy of the produced output to keep all that they did during the course. The package comes with a vignette describing how to write HTML reports for statistical analysis. Finally, a driver for Sweave parses HTML flat files containing R code and to automatically write the corresponding outputs (tables and graphs).
This package provides functions for extracting feature contributions from a random forest model from package randomForest. Feature contributions provide detailed information about the relationship between data variables and the predicted value returned by random forest model.
Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as glm. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
The pscl is an R package providing classes and methods for:
Bayesian analysis of roll call data (item-response models);
elementary Bayesian statistics;
maximum likelihood estimation of zero-inflated and hurdle models for count data;
utility functions.
This package provides qualitatively constrained (regression) smoothing splines via linear programming and sparse matrices.
This package provides interactive plotting functions for use within RStudio. The manipulate function accepts a plotting expression and a set of controls (e.g. slider, picker, checkbox, or button) which are used to dynamically change values within the expression. When a value is changed using its corresponding control the expression is automatically re-executed and the plot is redrawn.
The vegan package provides tools for descriptive community ecology. It has most basic functions of diversity analysis, community ordination and dissimilarity analysis. Most of its multivariate tools can be used for other data types as well.
This package provides an R wrapper of OpenAI API endpoints (see https://platform.openai.com/docs/introduction for details). This package covers Models, Completions, Chat, Edits, Images, Embeddings, Audio, Files, Fine-tunes, Moderations, and legacy Engines endpoints.
This package provides a Database Interface (DBI) compliant driver for R to access PostgreSQL database systems.
This package provides an efficient implementation of Kernel SHAP (Lundberg and Lee, 2017, <doi:10.48550/arXiv.1705.07874>) permutation SHAP, and additive SHAP for model interpretability. For Kernel SHAP and permutation SHAP, if the number of features is too large for exact calculations, the algorithms iterate until the SHAP values are sufficiently precise in terms of their standard errors. The package integrates smoothly with meta-learning packages such as tidymodels, caret or mlr3. It supports multi-output models, case weights, and parallel computations. Visualizations can be done using the R package shapviz.
This package provides syntax highlighting of R code, specifically designed for the needs of RMarkdown packages like pkgdown, hugodown, and bookdown. It includes linking of function calls to their documentation on the web, and automatic translation of ANSI escapes in output to the equivalent HTML.
The package provides estimators of the mode of univariate unimodal (and sometimes multimodal) data and values of the modes of usual probability distributions.
This package provides basic infrastructure and some algorithms for the traveling salesperson problem(TSP) (also known as the traveling salesman problem).
This package provides functions to calculate: moments, Pearson's kurtosis, Geary's kurtosis and skewness; it also includes tests related to them (Anscombe-Glynn, D'Agostino, Bonett-Seier).
R-wrs2 offers a range of strong stats methods from Wilcox WRS functions. It implements robust t-tests, both independent and dependent, robust ANOVA, including designs with between-within subjects, quantile ANOVA, robust correlation, robust mediation, and nonparametric ANCOVA models using robust location measures.
This package provides classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
This package provides implementations of the SHA-3 cryptographic hash and SHAKE256 extendable-output functions (XOF).