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r-samurais
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Provides a variety of original and flexible user-friendly statistical latent variable models and unsupervised learning algorithms to segment and represent time-series data (univariate or multivariate), and more generally, longitudinal data, which include regime changes. 'samurais' is built upon the following packages, each of them is an autonomous time-series segmentation approach: Regression with Hidden Logistic Process ('RHLP'), Hidden Markov Model Regression ('HMMR'), Multivariate 'RHLP' ('MRHLP'), Multivariate 'HMMR' ('MHMMR'), Piece-Wise regression ('PWR'). For the advantages/differences of each of them, the user is referred to our mentioned paper references.
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2025-04-22 |
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r-samplingvarest
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Functions to calculate some point estimators and estimate their variance under unequal probability sampling without replacement. Single and two-stage sampling designs are considered. Some approximations for the second-order inclusion probabilities (joint inclusion probabilities) are available (sample and population based). A variety of Jackknife variance estimators are implemented. Almost every function is written in C (compiled) code for faster results. The functions incorporate some performance improvements for faster results with large datasets.
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2025-04-22 |
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r-sampling
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Functions to draw random samples using different sampling schemes are available. Functions are also provided to obtain (generalized) calibration weights, different estimators, as well some variance estimators.
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2025-04-22 |
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r-s2
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Provides R bindings for Google's s2 library for geometric calculations on the sphere. High-performance constructors and exporters provide high compatibility with existing spatial packages, transformers construct new geometries from existing geometries, predicates provide a means to select geometries based on spatial relationships, and accessors extract information about geometries.
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2025-04-22 |
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r-samplingbigdata
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Select sampling methods for probability samples using large data sets. This includes spatially balanced sampling in multi-dimensional spaces with any prescribed inclusion probabilities. All implementations are written in C with efficient data structures such as k-d trees that easily scale to several million rows on a modern desktop computer.
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2025-04-22 |
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r-ryacas
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Interface to the 'yacas' computer algebra system (<http://www.yacas.org/>).
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2025-04-22 |
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r-rvcg
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Operations on triangular meshes based on 'VCGLIB'. This package integrates nicely with the R-package 'rgl' to render the meshes processed by 'Rvcg'. The Visualization and Computer Graphics Library (VCG for short) is an open source portable C++ templated library for manipulation, processing and displaying with OpenGL of triangle and tetrahedral meshes. The library, composed by more than 100k lines of code, is released under the GPL license, and it is the base of most of the software tools of the Visual Computing Lab of the Italian National Research Council Institute ISTI <http://vcg.isti.cnr.it>, like 'metro' and 'MeshLab'. The 'VCGLIB' source is pulled from trunk <https://github.com/cnr-isti-vclab/vcglib> and patched to work with options determined by the configure script as well as to work with the header files included by 'RcppEigen'.
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2025-04-22 |
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r-runuran
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Interface to the 'UNU.RAN' library for Universal Non-Uniform RANdom variate generators. Thus it allows to build non-uniform random number generators from quite arbitrary distributions. In particular, it provides an algorithm for fast numerical inversion for distribution with given density function. In addition, the package contains densities, distribution functions and quantiles from a couple of distributions.
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2025-04-22 |
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r-ruimtehol
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Wraps the 'StarSpace' library <https://github.com/facebookresearch/StarSpace> allowing users to calculate word, sentence, article, document, webpage, link and entity 'embeddings'. By using the 'embeddings', you can perform text based multi-label classification, find similarities between texts and categories, do collaborative-filtering based recommendation as well as content-based recommendation, find out relations between entities, calculate graph 'embeddings' as well as perform semi-supervised learning and multi-task learning on plain text. The techniques are explained in detail in the paper: 'StarSpace: Embed All The Things!' by Wu et al. (2017), available at <arXiv:1709.03856>.
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2025-04-22 |
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r-runner
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Lightweight library for rolling windows operations. Package enables full control over the window length, window lag and a time indices. With a runner one can apply any R function on a rolling windows. The package eases work with equally and unequally spaced time series.
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2025-04-22 |
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r-rucrdtw
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R bindings for functions from the UCR Suite by Rakthanmanon et al. (2012) <DOI:10.1145/2339530.2339576>, which enables ultrafast subsequence search for a best match under Dynamic Time Warping and Euclidean Distance.
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2025-04-22 |
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r-rttf2pt1
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Contains the program 'ttf2pt1', for use with the 'extrafont' package. This product includes software developed by the 'TTF2PT1' Project and its contributors.
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2025-04-22 |
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r-rtsne
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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).
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2025-04-22 |
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r-rtriangle
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This is a port of Jonathan Shewchuk's Triangle library to R. From his description: "Triangle generates exact Delaunay triangulations, constrained Delaunay triangulations, conforming Delaunay triangulations, Voronoi diagrams, and high-quality triangular meshes. The latter can be generated with no small or large angles, and are thus suitable for finite element analysis."
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2025-04-22 |
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r-rtkore
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'STK++' <http://www.stkpp.org> is a collection of C++ classes for statistics, clustering, linear algebra, arrays (with an 'Eigen'-like API), regression, dimension reduction, etc. The integration of the library to 'R' is using 'Rcpp'. The 'rtkore' package includes the header files from the 'STK++' core library. All files contain only template classes and/or inline functions. 'STK++' is licensed under the GNU LGPL version 2 or later. 'rtkore' (the 'stkpp' integration into 'R') is licensed under the GNU GPL version 2 or later. See file LICENSE.note for details.
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2025-04-22 |
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r-rtk
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Rarefy data, calculate diversity and plot the results.
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2025-04-22 |
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r-rstream
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Unified object oriented interface for multiple independent streams of random numbers from different sources.
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2025-04-22 |
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r-rstiefel
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Simulation of random orthonormal matrices from linear and quadratic exponential family distributions on the Stiefel manifold. The most general type of distribution covered is the matrix-variate Bingham-von Mises-Fisher distribution. Most of the simulation methods are presented in Hoff(2009) "Simulation of the Matrix Bingham-von Mises-Fisher Distribution, With Applications to Multivariate and Relational Data" <doi:10.1198/jcgs.2009.07177>. The package also includes functions for optimization on the Stiefel manifold based on algorithms described in Wen and Yin (2013) "A feasible method for optimization with orthogonality constraints" <doi:10.1007/s10107-012-0584-1>.
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2025-04-22 |
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r-rsyslog
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Functions to write messages to the 'syslog' system logger API, available on all 'POSIX'-compatible operating systems. Features include tagging messages with a priority level and application type, as well as masking (hiding) messages below a given priority level.
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2025-04-22 |
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r-rspectra
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R interface to the 'Spectra' library <https://spectralib.org/> for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n. This package provides the 'eigs()' function that does the similar job as in 'Matlab', 'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function to calculate the largest k singular values and corresponding singular vectors of a real matrix. The matrix to be computed on can be dense, sparse, or in the form of an operator defined by the user.
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2025-04-22 |
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r-rsnns
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The Stuttgart Neural Network Simulator (SNNS) is a library containing many standard implementations of neural networks. This package wraps the SNNS functionality to make it available from within R. Using the 'RSNNS' low-level interface, all of the algorithmic functionality and flexibility of SNNS can be accessed. Furthermore, the package contains a convenient high-level interface, so that the most common neural network topologies and learning algorithms integrate seamlessly into R.
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2025-04-22 |
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r-rsiena
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The main purpose of this package is to perform simulation-based estimation of stochastic actor-oriented models for longitudinal network data collected as panel data. Dependent variables can be single or multivariate networks, which can be directed, non-directed, or two-mode; and associated actor variables. There are also functions for testing parameters and checking goodness of fit. An overview of these models is given in Tom A.B. Snijders (2017), Stochastic Actor-Oriented Models for Network Dynamics, Annual Review of Statistics and Its Application, 4, 343-363 <doi: 10.1146/annurev-statistics-060116-054035>. An extensive manual, scripts, and much further information is at the Siena website <http://www.stats.ox.ac.uk/~snijders/siena/>.
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2025-04-22 |
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r-rsdepth
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Ray Shooting Depth functions are provided for bivariate analysis. This mainly includes functions for computing the bivariate depth as well as RS median. Drawing functions for depth bags are also provided.
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2025-04-22 |
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r-rscimark
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The SciMark 2.0 benchmark was originally developed in Java as a benchmark for numerical and scientific computational performance. It measures the performance of several computational kernels which are frequently occurring in scientific applications. This package is a simple wrapper around the ANSI C implementation of the benchmark.
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2025-04-22 |
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r-rsclient
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Client for Rserve, allowing to connect to Rserve instances and issue commands.
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2025-04-22 |
