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Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.
Extension of `data.frame`
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Extended Model Formulas
Infrastructure for extended formulas with multiple parts on the
right-hand side and/or multiple responses on the left-hand side
(see
A Toolbox for Manipulating and Assessing Colors and Palettes
Carries out 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 along with corresponding ggplot2 color scales.
Color palette choice is aided by an interactive app (with either a Tcl/Tk
or a shiny graphical user interface) and shiny apps with an HCL color picker and a
color vision deficiency emulator. Plotting functions for displaying
and assessing palettes include color swatches, visualizations of the
HCL space, and trajectories in HCL and/or RGB spectrum. Color manipulation
functions include: desaturation, lightening/darkening, mixing, and
simulation of color vision deficiencies (deutanomaly, protanomaly, tritanomaly).
Details can be found on the project web page at < https://colorspace.R-Forge.R-project.org/>
and in the accompanying scientific paper: Zeileis et al. (2020, Journal of Statistical
Software,
Tools for Parsing and Generating XML Within R and S-Plus
Many approaches for both reading and creating XML (and HTML) documents (including DTDs), both local and accessible via HTTP or FTP. Also offers access to an 'XPath' "interpreter".
Trellis Graphics for R
A powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements. See ?Lattice for an introduction.
Simple Data Frames
Provides a 'tbl_df' class (the 'tibble') with stricter checking and better formatting than the traditional data frame.
Render Markdown with 'commonmark'
Render Markdown to full and lightweight HTML/LaTeX documents with the 'commonmark' package. This package has been superseded by 'litedown'.
Multivariate Normal and t Distributions
Computes multivariate normal and t probabilities, quantiles, random deviates, and densities. Log-likelihoods for multivariate Gaussian models and Gaussian copulae parameterised by Cholesky factors of covariance or precision matrices are implemented for interval-censored and exact data, or a mix thereof. Score functions for these log-likelihoods are available. A class representing multiple lower triangular matrices and corresponding methods are part of this package.
Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien
Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, generalized k-nearest neighbour ...