This package provides ggplot2 geoms filled with various patterns. It includes a patterned version of every ggplot2 geom that has a region that can be filled with a pattern. It provides a suite of ggplot2 aesthetics and scales for controlling pattern appearances. It supports over a dozen builtin patterns (every pattern implemented by gridpattern) as well as allowing custom user-defined patterns.

Facilitates easy analysis of factorial experiments, including purely within-Ss designs (a.k.a. "repeated measures"), purely between-Ss designs, and mixed within-and-between-Ss designs. The functions in this package aim to provide simple, intuitive and consistent specification of data analysis and visualization. Visualization functions also include design visualization for pre-analysis data auditing, and correlation matrix visualization. Finally, this package includes functions for non-parametric analysis, including permutation tests and bootstrap resampling. The bootstrap function obtains predictions either by cell means or by more advanced/powerful mixed effects models, yielding predictions and confidence intervals that may be easily visualized at any level of the experiment's design.

This package provides type-stable rolling window functions over any R data type. Cumulative and expanding windows are also supported. For more advanced usage, an index can be used as a secondary vector that defines how sliding windows are to be created.

The analysis and inference of faunal remains recovered from archaeological sites concerns the field of zooarchaeology. The zooaRch package provides analytical tools to make inferences on zooarchaeological data. Functions in this package allow users to read, manipulate, visualize, and analyze zooarchaeological data.

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 provides functions for assessing the replication/preservation of a network module's topology across datasets through permutation testing.

This package extends the out of memory vectors of ff with statistical functions and other utilities to ease their usage.

This package provides functions and datasets for the book "Modern Applied Statistics with S" (4th edition, 2002) by Venables and Ripley.

Graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors.

This package provides tools to find the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library. There is support for approximate as well as exact searches, fixed radius searches and bd as well as kd trees. The distance is computed using the L1 (Manhattan, taxicab) metric.

This is a package for exploratory graphical analysis of multivariate data, specifically gene expression data with different projection methods: principal component analysis, correspondence analysis, spectral map analysis.

This package provides tools for maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting. It extends the lme4 package.

This package provides tools to render DOT diagram markup language in R and also provides the possibility to export the graphs in PostScript and SVG (Scalable Vector Graphics) formats. In addition, it supports literate programming packages such as knitr and rmarkdown.

This package provides a common framework for optimization of black-box functions for other packages, e.g. mlr3. It offers various optimization methods e.g. grid search, random search and generalized simulated annealing.

This package provides a quantitative financial modelling framework to allow users to specify, build, trade, and analyse quantitative financial trading strategies.

This package provides tools to access and manipulate Word and PowerPoint documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. When working with PowerPoint presentations, slides can be added or removed; shapes inside slides can also be added or removed. When working with Word documents, a cursor can be used to help insert or delete content at a specific location in the document.

A treemap is a space-filling visualization of hierarchical structures. This package offers great flexibility to draw treemaps.

This package provides several utility functions for the book entitled "Practices of Medical and Health Data Analysis using R" (Pearson Education Japan, 2007) with Japanese demographic data and some demographic analysis related functions.

The R package ggplot2 is a plotting system based on the grammar of graphics. GGally extends ggplot2 by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.

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 is a package for parameter description and operations in optimization, tuning and machine learning. Parameters can be described (type, constraints, defaults, etc.), combined to parameter sets and can in general be programmed on. A useful OptPath object (archive) to log function evaluations is also provided.

This package lets you fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.

This package implements list environments. List environments are environments that have list-like properties. For instance, the elements of a list environment are ordered and can be accessed and iterated over using index subsetting.

Multivariate data analysis is the simultaneous observation of more than one characteristic. In contrast to the analysis of univariate data, in this approach not only a single variable or the relation between two variables can be investigated, but the relations between many attributes can be considered. For the statistical analysis of chemical data one has to take into account the special structure of this type of data. This package contains about 30 functions, mostly for regression, classification and model evaluation and includes some data sets used in the R help examples. It was designed as a R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009).