Miscellaneous Functions for 'SciViews::R'

Functions required for the 'SciViews::R' dialect or for general use: manage a temporary environment attached to the search path, define synonyms for R functions using aka(), test if 'Aqua', 'Mac', 'Win' ... Show progress bar, etc.

Take Screenshots of Web Pages

Takes screenshots of web pages, including Shiny applications and R Markdown documents.

Syntax Highlighter

Syntax highlighter for R code based on the results of the R parser. Rendering in HTML and latex markup. Custom Sweave driver performing syntax highlighting of R code chunks.

Base Package for Phylogenetic Structures and Comparative Data

Provides a base S4 class for comparative methods, incorporating one or more trees and trait data.

Mixed-Effect Models, with or without Spatial Random Effects

Inference based on models with or without spatially-correlated random effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy 2014 ), and Markov random field models on irregular grids (as considered in the 'INLA' package, < https://www.r-inla.org>), can be fitted, with distinct computational procedures exploiting the sparse matrix representations for the latter case and other autoregressive models. Laplace approximations are used for likelihood or restricted likelihood. Penalized quasi-likelihood and other variants discussed in the h-likelihood literature (Lee and Nelder 2001 ) are also implemented.

Additional Binary Operators

A set of binary operators for common tasks such as regex manipulation.

Multivariate Exploratory Data Analysis and Data Mining

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. F. Husson, S. Le and J. Pages (2017).

Handling Missing Values with Multivariate Data Analysis

Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA or MCA.

Extension to 'ggplot2'

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.

Retrieve Code Decorations

Retrieves code comment decorations for C++ languages of the form '\\ [[xyz]]', which are used for automated wrapping of C++ functions.