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r-semicomprisks
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Hierarchical multistate models are considered to perform the analysis of independent/clustered semi-competing risks data. The package allows to choose the specification for model components from a range of options giving users substantial flexibility, including: accelerated failure time or proportional hazards regression models; parametric or non-parametric specifications for baseline survival functions and cluster-specific random effects distribution; a Markov or semi-Markov specification for terminal event following non-terminal event. While estimation is mainly performed within the Bayesian paradigm, the package also provides the maximum likelihood estimation approach for several parametric models. The package also includes functions for univariate survival analysis as complementary analysis tools.
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2025-03-25 |
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r-sel
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Implements a method for fitting a bounded probability distribution to quantiles (for example stated by an expert), see Bornkamp and Ickstadt (2009) for details. For this purpose B-splines are used, and the density is obtained by penalized least squares based on a Brier entropy penalty. The package provides methods for fitting the distribution as well as methods for evaluating the underlying density and cdf. In addition methods for plotting the distribution, drawing random numbers and calculating quantiles of the obtained distribution are provided.
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2025-03-25 |
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r-seismicroll
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public |
Fast versions of seismic analysis functions that 'roll' over a vector of values. See the 'RcppRoll' package for alternative versions of basic statistical functions such as rolling mean, median, etc.
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2025-03-25 |
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r-segmgarch
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Implements a segmentation algorithm for multiple change-point detection in high-dimensional GARCH processes. It simultaneously segments GARCH processes by identifying 'common' change-points, each of which can be shared by a subset or all of the component time series as a change-point in their within-series and/or cross-sectional correlation structure.
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2025-03-25 |
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r-segmentr
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Given a likelihood provided by the user, this package applies it to a given matrix dataset in order to find change points in the data that maximize the sum of the likelihoods of all the segments. This package provides a handful of algorithms with different time complexities and assumption compromises so the user is able to choose the best one for the problem at hand. The implementation of the segmentation algorithms in this package are based on the paper by Bruno M. de Castro, Florencia Leonardi (2018) <arXiv:1501.01756>. The Berlin weather sample dataset was provided by Deutscher Wetterdienst <https://dwd.de/>. You can find all the references in the Acknowledgments section of this package's repository via the URL below.
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2025-03-25 |
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r-segmentor3isback
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Performs a fast exact segmentation on data and allows for use of various cost functions.
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2025-03-25 |
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r-segmentier
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A dynamic programming solution to segmentation based on maximization of arbitrary similarity measures within segments. The general idea, theory and this implementation are described in Machne, Murray & Stadler (2017) <doi:10.1038/s41598-017-12401-8>. In addition to the core algorithm, the package provides time-series processing and clustering functions as described in the publication. These are generally applicable where a `k-means` clustering yields meaningful results, and have been specifically developed for clustering of the Discrete Fourier Transform of periodic gene expression data (`circadian' or `yeast metabolic oscillations'). This clustering approach is outlined in the supplemental material of Machne & Murray (2012) <doi:10.1371/journal.pone.0037906>), and here is used as a basis of segment similarity measures. Notably, the time-series processing and clustering functions can also be used as stand-alone tools, independent of segmentation, e.g., for transcriptome data already mapped to genes.
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2025-03-25 |
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r-segmag
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Contains functions that help to determine event boundaries in event segmentation experiments by bootstrapping a critical segmentation magnitude under the null hypothesis that all key presses were randomly distributed across the experiment. Segmentation magnitude is defined as the sum of Gaussians centered at the times of the segmentation key presses performed by the participants. Within a participant, the maximum of the overlaid Gaussians is used to prevent an excessive influence of a single participant on the overall outcome (e.g. if a participant is pressing the key multiple times in succession). Further functions are included, such as plotting the results.
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2025-03-25 |
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r-securitytxt
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When security risks in web services are discovered by independent security researchers who understand the severity of the risk, they often lack the channels to properly disclose them. As a result, security issues may be left unreported. The 'security.txt' 'Web Security Policies' specification defines an 'IETF' draft standard <https://tools.ietf.org/html/draft-foudil-securitytxt-00> to help organizations define the process for security researchers to securely disclose security vulnerabilities. Tools are provided to help identify and parse 'security.txt' files to enable analysis of the usage and adoption of these policies.
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2025-03-25 |
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r-secure
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public |
Sequential factor extraction via co-sparse unit-rank estimation (SeCURE).
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2025-03-25 |
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r-secr
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public |
Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.
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2025-03-25 |
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r-seas
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public |
Capable of deriving seasonal statistics, such as "normals", and analysis of seasonal data, such as departures. This package also has graphics capabilities for representing seasonal data, including boxplots for seasonal parameters, and bars for summed normals. There are many specific functions related to climatology, including precipitation normals, temperature normals, cumulative precipitation departures and precipitation interarrivals. However, this package is designed to represent any time-varying parameter with a discernible seasonal signal, such as found in hydrology and ecology.
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2025-03-25 |
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r-searchtrees
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public |
The QuadTree data structure is useful for fast, neighborhood-restricted lookups. We use it to implement fast k-Nearest Neighbor and Rectangular range lookups in 2 dimenions. The primary target is high performance interactive graphics.
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2025-03-25 |
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r-sdwd
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Formulates a sparse distance weighted discrimination (SDWD) for high-dimensional classification and implements a very fast algorithm for computing its solution path with the L1, the elastic-net, and the adaptive elastic-net penalties. More details about the methodology SDWD is seen on Wang and Zou (2016) (<doi:10.1080/10618600.2015.1049700>).
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2025-03-25 |
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r-sdpt3r
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Solves the general Semi-Definite Linear Programming formulation using an R implementation of SDPT3 (K.C. Toh, M.J. Todd, and R.H. Tutuncu (1999) <doi:10.1080/10556789908805762>). This includes problems such as the nearest correlation matrix problem (Higham (2002) <doi:10.1093/imanum/22.3.329>), D-optimal experimental design (Smith (1918) <doi:10.2307/2331929>), Distance Weighted Discrimination (Marron and Todd (2012) <doi:10.1198/016214507000001120>), as well as graph theory problems including the maximum cut problem. Technical details surrounding SDPT3 can be found in R.H Tutuncu, K.C. Toh, and M.J. Todd (2003) <doi:10.1007/s10107-002-0347-5>.
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2025-03-25 |
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r-sdnet
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public |
Fitting discrete Bayesian networks using soft-discretized data. Soft-discretization is based on mixture of normal distributions. Also implemented is a supervised Bayesian network learning employing Kullback-Leibler divergence. For more information see Balov (2013) <DOI:10.1186/1755-8794-6-S3-S1>.
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2025-03-25 |
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r-sdde
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Compares the evolution of an original network X to an augmented network Y by counting the number of Shortcuts, Detours, Dead Ends (SDDE), equal paths and disconnected nodes.
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2025-03-25 |
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r-sdat
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Test the global null in linear models using marginal approach.
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2025-03-25 |
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r-rcppxsimd
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This header-only library provides modern, portable C++ wrappers for SIMD intrinsics and parallelized, optimized math implementations (SSE, AVX, NEON, AVX512). By placing this library in this package, we offer an efficient distribution system for Xsimd <https://github.com/xtensor-stack/xsimd> for R packages using CRAN.
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2025-03-25 |
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r-rcppgetconf
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The 'getconf' command-line tool provided by 'libc' allows querying of a large number of system variables. This package provides similar functionality.
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2025-03-25 |
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r-rborist
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Scalable implementation of classification and regression forests, as described by Breiman (2001), <DOI:10.1023/A:1010933404324>.
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2025-03-25 |
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r-readstata13
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Function to read and write the 'Stata' file format.
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2025-03-25 |
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r-readsdmx
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Read Statistical Data and Metadata Exchange (SDMX) XML data. This the main transmission format used in official statistics. Data can be imported from local SDMX-ML files or a SDMX web-service and will be read in 'as is' into a dataframe object. The 'RapidXML' C++ library <https://rapidxml.sourceforge.net/> is used to parse the XML data.
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2025-03-25 |
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r-readobj
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Wraps 'tiny_obj_loader' C++ library for reading the 'Wavefront' OBJ 3D file format including both mesh objects and materials files. The resultant R objects are either structured to match the 'tiny_obj_loader' internal data representation or in a form directly compatible with the 'rgl' package.
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2025-03-25 |
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r-read.dbc
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Functions for reading and decompressing the DBC (compressed DBF) files. Please note that this is the file format used by the Brazilian Ministry of Health (DATASUS) to publish healthcare datasets. It is not related to the FoxPro or CANdb DBC file formats.
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2025-03-25 |
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r-rdtq
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Implementation of density tracking by quadrature (DTQ) algorithms for stochastic differential equations (SDEs). DTQ algorithms numerically compute the density function of the solution of an SDE with user-specified drift and diffusion functions. The calculation does not require generation of sample paths, but instead proceeds in a deterministic fashion by repeatedly applying quadrature to the Chapman-Kolmogorov equation associated with a discrete-time approximation of the SDE. The DTQ algorithm is provably convergent. For several practical problems of interest, we have found the DTQ algorithm to be fast, accurate, and easy to use.
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2025-03-25 |
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r-rdsdp
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R interface to DSDP semidefinite programming library. The DSDP software is a free open source implementation of an interior-point method for semidefinite programming. It provides primal and dual solutions, exploits low-rank structure and sparsity in the data, and has relatively low memory requirements for an interior-point method.
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2025-03-25 |
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r-rdist
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A common framework for calculating distance matrices.
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2025-03-25 |
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r-rdieharder
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The 'RDieHarder' package provides an R interface to the 'DieHarder' suite of random number generators and tests that was developed by Robert G. Brown and David Bauer, extending earlier work by George Marsaglia and others. The 'DieHarder' library code is included.
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2025-03-25 |
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r-rcsf
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Cloth Simulation Filter (CSF) is an airborne LiDAR (Light Detection and Ranging) ground points filtering algorithm which is based on cloth simulation. It tries to simulate the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface <https://www.mdpi.com/2072-4292/8/6/501/htm>.
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2025-03-25 |
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r-rcsdp
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R interface to the CSDP semidefinite programming library. Installs version 6.1.1 of CSDP from the COIN-OR website if required. An existing installation of CSDP may be used by passing the proper configure arguments to the installation command. See the INSTALL file for further details.
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2025-03-25 |
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r-rcrm
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Fit a 2-parameter continual reassessment method (CRM) model (O'Quigley and Shen (1996), <doi: 10.2307/2532905>) regularized with L2 norm (Friedman et al. (2010), <doi: 10.18637/jss.v033.i01>) adjusted by the distance with the target dose limiting toxicity (DLT) rate.
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2025-03-25 |
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r-rcppxts
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Access to some of the C level functions of the 'xts' package. In its current state, the package is mostly a proof-of-concept to support adding useful functions, and does not yet add any of its own.
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2025-03-25 |
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r-rcpptoml
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The configuration format defined by 'TOML' (which expands to "Tom's Obvious Markup Language") specifies an excellent format (described at <https://toml.io/en/>) suitable for both human editing as well as the common uses of a machine-readable format. This package uses 'Rcpp' to connect to the 'toml++' parser written by Mark Gillard to R.
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2025-03-25 |
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r-rcpptn
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R-level and C++-level functionality to generate random deviates from and calculate moments of a Truncated Normal distribution using the algorithm of Robert (1995) <DOI:10.1007/BF00143942>. In addition to RNG, functions for calculating moments, densities, and entropies are provided at both levels.
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2025-03-25 |
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r-rcppstreams
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The 'Streamulus' (template, header-only) library by Irit Katriel (at <https://github.com/iritkatriel/streamulus>) provides a very powerful yet convenient framework for stream processing. This package connects 'Streamulus' to R by providing both the header files and all examples.
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2025-03-25 |
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r-rcppsmc
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R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.
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2025-03-25 |
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r-rcppquantuccia
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'QuantLib' bindings are provided for R using 'Rcpp' via an updated variant of the header-only 'Quantuccia' project (put together initially by Peter Caspers) offering an essential subset of 'QuantLib' (and now maintained separately for the calendaring subset). See the included file 'AUTHORS' for a full list of contributors to both 'QuantLib' and 'Quantuccia'.
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2025-03-25 |
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r-rcppparallel
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High level functions for parallel programming with 'Rcpp'. For example, the 'parallelFor()' function can be used to convert the work of a standard serial "for" loop into a parallel one and the 'parallelReduce()' function can be used for accumulating aggregate or other values.
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2025-03-25 |
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r-rcppnumerical
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A collection of open source libraries for numerical computing (numerical integration, optimization, etc.) and their integration with 'Rcpp'.
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2025-03-25 |
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r-rcppnloptexample
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An example package which shows use of 'NLopt' functionality from C++ via 'Rcpp' without requiring linking, and relying just on 'nloptr' thanks to the exporting API added there by Jelmer Ypma. This package is a fully functioning, updated, and expanded version of the initial example by Julien Chiquet at <https://github.com/jchiquet/RcppArmadilloNLoptExample> also containing a large earlier pull request of mine.
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2025-03-25 |
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r-rcppmsgpack
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'MsgPack' header files are provided for use by R packages, along with the ability to access, create and alter 'MsgPack' objects directly from R. 'MsgPack' is an efficient binary serialization format. It lets you exchange data among multiple languages like 'JSON' but it is faster and smaller. Small integers are encoded into a single byte, and typical short strings require only one extra byte in addition to the strings themselves. This package provides headers from the 'msgpack-c' implementation for C and C++(11) for use by R, particularly 'Rcpp'. The included 'msgpack-c' headers are licensed under the Boost Software License (Version 1.0); the code added by this package as well the R integration are licensed under the GPL (>= 2). See the files 'COPYRIGHTS' and 'AUTHORS' for a full list of copyright holders and contributors to 'msgpack-c'.
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2025-03-25 |
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r-rcpphungarian
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Header library and R functions to solve minimum cost bipartite matching problem using Huhn-Munkres algorithm (Hungarian algorithm; <https://en.wikipedia.org/wiki/Hungarian_algorithm>; Kuhn (1955) <doi:10.1002/nav.3800020109>). This is a repackaging of code written by Cong Ma in the GitHub repo <https://github.com/mcximing/hungarian-algorithm-cpp>.
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2025-03-25 |
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r-rcpphnsw
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'Hnswlib' is a C++ library for Approximate Nearest Neighbors. This package provides a minimal R interface by relying on the 'Rcpp' package. See <https://github.com/nmslib/hnswlib> for more on 'hnswlib'. 'hnswlib' is released under Version 2.0 of the Apache License.
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2025-03-25 |
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r-rcpphmm
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Collection of functions to evaluate sequences, decode hidden states and estimate parameters from a single or multiple sequences of a discrete time Hidden Markov Model. The observed values can be modeled by a multinomial distribution for categorical/labeled emissions, a mixture of Gaussians for continuous data and also a mixture of Poissons for discrete values. It includes functions for random initialization, simulation, backward or forward sequence evaluation, Viterbi or forward-backward decoding and parameter estimation using an Expectation-Maximization approach.
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2025-03-25 |
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r-rcppgsl
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'Rcpp' integration for 'GNU GSL' vectors and matrices The 'GNU Scientific Library' (or 'GSL') is a collection of numerical routines for scientific computing. It is particularly useful for C and C++ programs as it provides a standard C interface to a wide range of mathematical routines. There are over 1000 functions in total with an extensive test suite. The 'RcppGSL' package provides an easy-to-use interface between 'GSL' data structures and R using concepts from 'Rcpp' which is itself a package that eases the interfaces between R and C++. This package also serves as a prime example of how to build a package that uses 'Rcpp' to connect to another third-party library. The 'autoconf' script, 'inline' plugin and example package can all be used as a stanza to write a similar package against another library.
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2025-03-25 |
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r-rcppgreedysetcover
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A fast implementation of the greedy algorithm for the set cover problem using 'Rcpp'.
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2025-03-25 |
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r-rcppfaddeeva
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Access to a family of Gauss error functions for arbitrary complex arguments is provided via the 'Faddeeva' package by Steven G. Johnson (see <http://ab-initio.mit.edu/wiki/index.php/Faddeeva_Package> for more information).
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2025-03-25 |
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r-rcppexamples
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Examples for Seamless R and C++ integration The 'Rcpp' package contains a C++ library that facilitates the integration of R and C++ in various ways. This package provides some usage examples. Note that the documentation in this package currently does not cover all the features in the package. The site <http://gallery.rcpp.org> regroups a large number of examples for 'Rcpp'.
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2025-03-25 |
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r-rcppensmallen
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'Ensmallen' is a templated C++ mathematical optimization library (by the 'MLPACK' team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library and pairs the appropriate header files from 'armadillo' through the 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under similar terms. Note that 'Ensmallen' requires a compiler that supports 'C++11' and 'Armadillo' 9.800 or later.
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2025-03-25 |
