This package provides functions and scripts used in the book "Chemometrics with R - Multivariate Data Analysis in the Natural Sciences and Life Sciences" by Ron Wehrens, Springer (2011).

This package provides a set of fonts. This is useful when you want to avoid system fonts to make sure your outputs are reproducible.

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 provides a collection of functions to implement a class for univariate polynomial manipulations.

There are three main goals to the vctrs package:

1. To propose vec_size() and vec_type() as alternatives to length() and class(). These definitions are paired with a framework for type-coercion and size-recycling.

2. To define type- and size-stability as desirable function properties, use them to analyse existing base function, and to propose better alternatives. This work has been particularly motivated by thinking about the ideal properties of c(), ifelse(), and rbind().

3. To provide a new vctr base class that makes it easy to create new S3 vectors. vctrs provides methods for many base generics in terms of a few new vctrs generics, making implementation considerably simpler and more robust.

This package provides procedures for model-based trees for subgroup analyses in clinical trials and model-based forests for the estimation and prediction of personalised treatment effects. Currently partitioning of linear models, lm(), generalised linear models, glm(), and Weibull models, survreg(), are supported. Advanced plotting functionality is supported for the trees and a test for parameter heterogeneity is provided for the personalised models.

This package provides functions related to L-moments: computation of L-moments and trimmed L-moments of distributions and data samples; parameter estimation; L-moment ratio diagram; plot vs. quantiles of an extreme-value distribution.

This is an R package for spell checking common document formats including LaTeX, markdown, manual pages, and DESCRIPTION files. It includes utilities to automate checking of documentation and vignettes as a unit test during R CMD check. Both British and American English are supported out of the box and other languages can be added. In addition, packages may define a wordlist to allow custom terminology without having to abuse punctuation.

This is a package for fast and user-friendly estimation of econometric models with multiple fixed-effects. It includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018). It further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.

This package provides a simple method for representing a visual scene as it may be seen by an animal with less acute vision.

This is a pure R implementation of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) with optional restarts (IPOP-CMA-ES).

This package provides an infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). It also provides C implementations of the association mining algorithms Apriori and Eclat.

This package enables conversions between R objects and JavaScript Object Notation (JSON) using the rapidjsonr library.

This package lets you determine the significance of pre-defined sets of genes with respect to an outcome variable, such as a group indicator, a quantitative variable or a survival time.

Anti-Grain Geometry (AGG) is a high-quality and high-performance 2D drawing library. The ragg package provides a set of graphic devices based on AGG to use as alternative to the raster devices provided through the grDevices package.

This package provides classes and methods for spatial data; the classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc.

For distributions whose probability density functions are log-concave, the adaptive rejection sampling algorithm can be used to build envelope functions for sampling. For others, the modified adaptive rejection sampling algorithm, the concave-convex adaptive rejection sampling algorithm, and the adaptive slice sampling algorithm can be used. This R package mainly includes these four functions: rARS(), rMARS(), rCCARS(), and rASS(). These functions can realize sampling based on the algorithms above.

This package provides tools and functions for managing the download of binary files. Binary repositories are defined in the YAML format. Defining new pre-download, download and post-download templates allow additional repositories to be added.

This is a package for estimation of one-dimensional probability distributions including kernel density estimation, weighted empirical cumulative distribution functions, Kaplan-Meier and reduced-sample estimators for right-censored data, heat kernels, kernel properties, quantiles and integration.

R's default conflict management system gives the most recently loaded package precedence. This can make it hard to detect conflicts, particularly when they arise because a package update creates ambiguity that did not previously exist. The conflicted package takes a different approach, making every conflict an error and forcing you to choose which function to use.

The main function biclust() provides several algorithms to find biclusters in two-dimensional data, spectral, plaid model, xmotifs, and bimax. In addition, the package provides methods for data preprocessing (normalization and discretization), visualization, and validation of bicluster solutions.

This package provides counterparts to R string manipulation functions that account for the effects of ANSI text formatting control sequences.

This package provides a set of functions to generate high-resolution Venn and Euler plots. It includes handling for several special cases, including two-case scaling, and extensive customization of plot shape and structure.

This package provides a simple, consistent interface to working with XML files in R. It is built on top of the libxml2 C library.