This package provides features to build gradient color maps.

The Rmisc library contains functions for data analysis and utility operations.

This package provides visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).

Manipulate and visualize colors in a intuitive, low-dependency and functional way.

Several web services are available that provide access to elevation data. This package provides access to many of those services and returns elevation data either as an sf simple features object from point elevation services or as a raster object from raster elevation services.

This package provides exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis.

This package provides a complete unit test system and functions to implement its GUI part.

This package provides a system for generating extendable and customizable heatmaps for exploring complex datasets, including big data and data with multiple data types.

This package contains the core survival analysis routines, including definition of Surv objects, Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, and parametric accelerated failure time models.

This is a package for model fitting, optimal model selection and calculation of various features that are essential in the analysis of quantitative real-time polymerase chain reaction (qPCR).

For tree ensembles such as random forests, regularized random forests and gradient boosted trees, this package provides functions for: extracting, measuring and pruning rules; selecting a compact rule set; summarizing rules into a learner; calculating frequent variable interactions; formatting rules in latex code. Reference: Interpreting tree ensembles with inTrees (Houtao Deng, 2019, <doi:10.1007/s41060-018-0144-8>).

This package provides functions to compute quasi variances and associated measures of approximation error.

This package provides routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

This package can be used to compute local false discovery rates.

This package provides functions used for local regression, likelihood and density estimation.

This package provides tools to execute arbitrary R or C functions some time after the current time, after the R execution stack has emptied.

This package provides tools to compares k samples using the Anderson-Darling test, Kruskal-Wallis type tests with different rank score criteria, Steel's multiple comparison test, and the Jonckheere-Terpstra (JT) test. It computes asymptotic, simulated or (limited) exact P-values, all valid under randomization, with or without ties, or conditionally under random sampling from populations, given the observed tie pattern. Except for Steel's test and the JT test it also combines these tests across several blocks of samples.

The tidy modeling "verse" is a collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.

Read large text files by splitting them in smaller files. This package also provides some convenient wrappers around fread() and fwrite() from package data.table.

This package includes size measurements, clutch observations, and blood isotope ratios for adult foraging Adélie, Chinstrap, and Gentoo penguins observed on islands in the Palmer Archipelago near Palmer Station, Antarctica. Data were collected and made available by Dr. Kristen Gorman and the Palmer Station Long Term Ecological Research (LTER) Program.

This package provides tools for the estimation of indicators on social exclusion and poverty, as well as an implementation of Pareto tail modeling for empirical income distributions.

This package provides a collection of meta-analysis datasets for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.

This package provides gradient projection algorithms for factor rotation. For details see ?GPArotation.

This package performs angle-based outlier detection on a given data frame. It offers three methods to process data:

1. full but slow implementation using all the data that has cubic complexity;

2. a fully randomized method;

3. a method using k-nearest neighbours.

These algorithms are well suited for high dimensional data outlier detection.