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A Collection of Efficient and Extremely Fast R Functions II
A collection of fast statistical and utility functions for data analysis. Functions for regression, maximum likelihood, column-wise statistics and many more have been included. C++ has been utilized to speed up the functions. References: Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1
T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut Implementation
An R wrapper around the fast T-distributed Stochastic Neighbor Embedding implementation by Van der Maaten (see < https://github.com/lvdmaaten/bhtsne/> for more information on the original implementation).
Markov Chain Monte Carlo (MCMC) Package
Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return 'coda' mcmc objects that can then be summarized using the 'coda' package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
Regression Spline Functions and Classes
Constructs basis functions of B-splines, M-splines,
I-splines, convex splines (C-splines), periodic splines,
natural cubic splines, generalized Bernstein polynomials,
their derivatives, and integrals (except C-splines)
by closed-form recursive formulas.
It also contains a C++ head-only library integrated with Rcpp.
See Wang and Yan (2021)
Mining Association Rules and Frequent Itemsets
Provides the infrastructure for representing, manipulating
and analyzing transaction data and patterns (frequent itemsets and
association rules). Also provides C implementations of the
association mining algorithms Apriori and Eclat. Hahsler, Gruen and
Hornik (2005)
Template Model Builder: A General Random Effect Tool Inspired by 'ADMB'
With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.
Split, Combine and Compress PDF Files
Content-preserving transformations transformations of PDF files such as split, combine, and compress. This package interfaces directly to the 'qpdf' C++ library < https://qpdf.sourceforge.io/> and does not require any command line utilities. Note that 'qpdf' does not read actual content from PDF files: to extract text and data you need the 'pdftools' package.
Polygon Clipping
R port of Angus Johnson's open source library 'Clipper'. Performs polygon clipping operations (intersection, union, set minus, set difference) for polygonal regions of arbitrary complexity, including holes. Computes offset polygons (spatial buffer zones, morphological dilations, Minkowski dilations) for polygonal regions and polygonal lines. Computes Minkowski Sum of general polygons. There is a function for removing self-intersections from polygon data.
Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests
Provides (1) pseudo random generators - general linear congruential generators,
multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister
algorithm (
High Performance Colour Space Manipulation
The encoding of colour can be handled in many different ways, using different colour spaces. As different colour spaces have different uses, efficient conversion between these representations are important. The 'farver' package provides a set of functions that gives access to very fast colour space conversion and comparisons implemented in C++, and offers speed improvements over the 'convertColor' function in the 'grDevices' package.