This package provides output formats and utilities for authoring books and technical documents with R Markdown.

This is a package for the manipulation of genetic data (SNPs). Computation of genetic relationship matrix (GRM) and dominance matrix, linkage disequilibrium (LD), and heritability with efficient algorithms for linear mixed models (AIREML).

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

This package provides miscellaneous small tools and utilities. Many of them facilitate the work with matrices, e.g. inserting rows or columns, creating symmetric matrices, or checking for semidefiniteness. Other tools facilitate the work with regression models, e.g. extracting the standard errors, obtaining the number of (estimated) parameters, or calculating R-squared values.

This package provides helper functions that act as wrappers to more advanced statistical methods with the advantage of having sane defaults for quick reporting.

This package contains routines and documentation for solving quadratic programming problems.

prospectr provides miscellaneous functions to preprocess spectroscopic data and conduct representative sample selection, or calibration sampling.

This package provides a light weight implementation of the standard distribution functions for the inverse gamma distribution, wrapping those for the gamma distribution in the stats package.

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 is a deprecated package for calculating pairwise multiple comparisons of mean rank sums. This package is superseded by the novel PMCMRplus package. The PMCMR package is no longer maintained, but kept for compatibility of dependent packages for some time.

The main function kcca implements a general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further cluster methods include hard competitive learning, neural gas, and QT clustering. There are numerous visualization methods for cluster results (neighborhood graphs, convex cluster hulls, barcharts of centroids, ...), and bootstrap methods for the analysis of cluster stability.

This package provides functions and data accompanying the second edition of the book "Data Mining with R, learning with case studies" by Luis Torgo, published by CRC Press.

This package carries out a mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB and polar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided.

This package provides logicless templating, with a syntax that is not limited to R.

This package provides a self-tuning spectral clustering method for single or multi-view data. Spectrum uses a new type of adaptive density aware kernel that strengthens connections in the graph based on common nearest neighbours. It uses a tensor product graph data integration and diffusion procedure to integrate different data sources and reduce noise. Spectrum uses either the eigengap or multimodality gap heuristics to determine the number of clusters. The method is sufficiently flexible so that a wide range of Gaussian and non-Gaussian structures can be clustered with automatic selection of K.

This package provides cover-tree and kd-tree fast k-nearest neighbor search algorithms. Related applications including KNN classification, regression and information measures are implemented.

Radix trees, or tries, are key-value data structures optimized for efficient lookups, similar in purpose to hash tables. This package provides an implementation of radix trees for use in R programming and in developing packages with Rcpp.

This package provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline.

This package provides streamlined data import and export infrastructure by making assumptions that the user is probably willing to make: import and export determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., stringsAsFactors=FALSE), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, convert, provides a simple method for converting between file types.

Implementation of the web-based Practical Meta-Analysis Effect Size Calculator from David B. Wilson in R. Based on the input, the effect size can be returned as standardized mean difference, Cohen's f, Hedges' g, Pearson's r or Fisher's transformation z, odds ratio or log odds, or eta squared effect size.

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 is a collection of econometric functions for performance and risk analysis. This package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.

This package provides functions to compute insolation on tilted surfaces, computes atmospheric transmittance and related parameters such as: Earth radius vector, declination, sunset and sunrise, daylength, equation of time, vector in the direction of the sun, vector normal to surface, and some atmospheric physics.

This is a companion package for the book "A Course in Statistics with R" (ISBN 978-1-119-15272-9.)