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r-smfsb
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Code and data for modelling and simulation of stochastic kinetic biochemical network models. It contains the code and data associated with the second and third editions of the book Stochastic Modelling for Systems Biology, published by Chapman & Hall/CRC Press.
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2023-06-16 |
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r-sharpdata
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Functions and data sets inspired by data sharpening - data perturbation to achieve improved performance in nonparametric estimation, as described in Choi, E., Hall, P. and Rousson, V. (2000) <doi:10.1214/aos/1015957396>. Capabilities for enhanced local linear regression function and derivative estimation are included, as well as an asymptotically correct iterated data sharpening estimator for any degree of local polynomial regression estimation. A cross-validation-based bandwidth selector is included which, in concert with the iterated sharpener, will often provide superior performance, according to a median integrated squared error criterion. Sample data sets are provided to illustrate function usage.
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2023-06-16 |
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r-rdotnet
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Low-level interface to '.NET' virtual machine along the lines of the R C .call interface. Can create '.NET' object, call methods, get or set properties, call static functions, etc.
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-rcppclassic
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The 'RcppClassic' package provides a deprecated C++ library which facilitates the integration of R and C++. New projects should use the new 'Rcpp' 'API' in the 'Rcpp' package.
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2023-06-16 |
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r-rcppapt
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The 'APT Package Management System' provides Debian and Debian-derived Linux systems with a powerful system to resolve package dependencies. This package offers access directly from R. This can only work on a system with a suitable 'libapt-pkg-dev' installation so functionality is curtailed if such a library is not found.
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2023-06-16 |
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r-raverage
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Implementation of the R-Average method for parameter estimation of averaging models of the Anderson's Information Integration Theory by Vidotto, G., Massidda, D., & Noventa, S. (2010) <https://www.uv.es/psicologica/articulos3FM.10/3Vidotto.pdf>.
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2023-06-16 |
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r-r2bayesx
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An R interface to estimate structured additive regression (STAR) models with 'BayesX'.
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2023-06-16 |
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r-qrjoint
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Joint estimation of quantile specific intercept and slope parameters in a linear regression setting.
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2023-06-16 |
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r-qap
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Implements heuristics for the Quadratic Assignment Problem (QAP). Currently only a simulated annealing heuristic is available.
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2023-06-16 |
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r-genepi
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Functions for Genetic Epi Methods Developed at MSKCC
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2023-06-16 |
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r-ga
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Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach.
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2023-06-16 |
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r-fuzzyranktests
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Does fuzzy tests and confidence intervals (following Geyer and Meeden, Statistical Science, 2005, <doi:10.1214/088342305000000340>) for sign test and Wilcoxon signed rank and rank sum tests.
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2023-06-16 |
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r-sparcl
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Implements the sparse clustering methods of Witten and Tibshirani (2010): "A framework for feature selection in clustering"; published in Journal of the American Statistical Association 105(490): 713-726.
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2023-06-16 |
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r-skat
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Functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.
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2023-06-16 |
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r-simmer
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A process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R. It is designed as a generic yet powerful framework. The architecture encloses a robust and fast simulation core written in 'C++' with automatic monitoring capabilities. It provides a rich and flexible R API that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type. Documentation about 'simmer' is provided by several vignettes included in this package, via the paper by Ucar, Smeets & Azcorra (2019, <doi:10.18637/jss.v090.i02>), and the paper by Ucar, Hernández, Serrano & Azcorra (2018, <doi:10.1109/MCOM.2018.1700960>); see 'citation("simmer")' for details.
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2023-06-16 |
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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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2023-06-16 |
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r-quotedargs
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A facility for writing functions that quote their arguments, may sometimes evaluate them in the environment where they were quoted, and may pass them as quoted to other functions.
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2023-06-16 |
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r-quantregforest
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Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles. It is particularly well suited for high-dimensional data. Predictor variables of mixed classes can be handled. The package is dependent on the package 'randomForest', written by Andy Liaw.
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2023-06-16 |
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r-gifski
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Multi-threaded GIF encoder written in Rust: <https://gif.ski/>. Converts images to GIF animations using pngquant's efficient cross-frame palettes and temporal dithering with thousands of colors per frame.
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2023-06-16 |
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r-gee
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Generalized Estimation Equation solver.
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2023-06-16 |
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r-fromo
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Fast, numerically robust computation of weighted moments via 'Rcpp'. Supports computation on vectors and matrices, and Monoidal append of moments. Moments and cumulants over running fixed length windows can be computed, as well as over time-based windows. Moment computations are via a generalization of Welford's method, as described by Bennett et. (2009) <doi:10.1109/CLUSTR.2009.5289161>.
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2023-06-16 |
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r-fractional
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The main function of this package allows numerical vector objects to be displayed with their values in vulgar fractional form. This is convenient if patterns can then be more easily detected. In some cases replacing the components of a numeric vector by a rational approximation can also be expected to remove some component of round-off error. The main functions form a re-implementation of the functions 'fractions' and 'rational' of the MASS package, but using a radically improved programming strategy.
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2023-06-16 |
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r-foptions
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Provides a collection of functions to valuate basic options. This includes the generalized Black-Scholes option, options on futures and options on commodity futures.
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2023-06-16 |
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r-flexclust
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The main function kcca implements a general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further cluster methods include hard competitive learning, neural gas, and QT clustering. There are numerous visualization methods for cluster results (neighborhood graphs, convex cluster hulls, barcharts of centroids, ...), and bootstrap methods for the analysis of cluster stability.
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2023-06-16 |
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r-spatgraphs
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Graphs (or networks) and graph component calculations for spatial locations in 1D, 2D, 3D etc.
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2023-06-16 |
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r-sm
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This is software linked to the book 'Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations' Oxford University Press.
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2023-06-16 |
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r-siminf
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Provides an efficient and very flexible framework to conduct data-driven epidemiological modeling in realistic large scale disease spread simulations. The framework integrates infection dynamics in subpopulations as continuous-time Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined time-points. Using C code for the numerical solvers and 'OpenMP' (if available) to divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make the package extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. The package contains template models and can be extended with user-defined models.
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2023-06-16 |
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r-seqmeta
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Computes necessary information to meta analyze region-based tests for rare genetic variants (e.g. SKAT, T1) in individual studies, and performs meta analysis.
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2023-06-16 |
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r-sel
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This package implements a novel 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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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-rcppdl
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This package is based on the C++ code from Yusuke Sugomori, which implements basic machine learning methods with many layers (deep learning), including dA (Denoising Autoencoder), SdA (Stacked Denoising Autoencoder), RBM (Restricted Boltzmann machine) and DBN (Deep Belief Nets).
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2023-06-16 |
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r-qz
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Generalized eigenvalues and eigenvectors use QZ decomposition (generalized Schur decomposition). The decomposition needs an N-by-N non-symmetric matrix A or paired matrices (A,B) with eigenvalues reordering mechanism. The decomposition functions are mainly based Fortran subroutines in complex*16 and double precision of LAPACK library (version 3.4.2. or later).
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2023-06-16 |
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r-glinternet
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Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical group-lasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015) <DOI:10.1080/10618600.2014.938812>.
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2023-06-16 |
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r-glamlasso
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Functions capable of performing efficient design matrix free penalized estimation in large scale 2 and 3-dimensional generalized linear array model framework. The generic glamlasso() function solves the penalized maximum likelihood estimation (PMLE) problem in a pure generalized linear array model (GLAM) as well as in a GLAM containing a non-tensor component. Currently Lasso or Smoothly Clipped Absolute Deviation (SCAD) penalized estimation is possible for the followings models: The Gaussian model with identity link, the Binomial model with logit link, the Poisson model with log link and the Gamma model with log link. Furthermore this package also contains two functions that can be used to fit special cases of GLAMs, see glamlassoRR() and glamlassoS(). The procedure underlying these functions is based on the gdpg algorithm from Lund et al. (2017) <doi:10.1080/10618600.2017.1279548>.
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2023-06-16 |
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r-geocount
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This package provides a variety of functions to analyze and model geostatistical count data with generalized linear spatial models, including 1) simulate and visualize the data; 2) posterior sampling with robust MCMC algorithms (in serial or parallel way); 3) perform prediction for unsampled locations; 4) conduct Bayesian model checking procedure to evaluate the goodness of fitting; 5) conduct transformed residual checking procedure. In the package, seamlessly embedded C++ programs and parallel computing techniques are implemented to speed up the computing processes.
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2023-06-16 |
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r-gammslice
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Uses a slice sampling-based Markov chain Monte Carlo to conduct Bayesian fitting and inference for generalized additive mixed models. Generalized linear mixed models and generalized additive models are also handled as special cases of generalized additive mixed models. The methodology and software is described in Pham, T.H. and Wand, M.P. (2018). Australian and New Zealand Journal of Statistics, 60, 279-330 <DOI:10.1111/ANZS.12241>.
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2023-06-16 |
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r-forecastsnsts
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Methods to compute linear h-step ahead prediction coefficients based on localised and iterated Yule-Walker estimates and empirical mean squared and absolute prediction errors for the resulting predictors. Also, functions to compute autocovariances for AR(p) processes, to simulate tvARMA(p,q) time series, and to verify an assumption from Kley et al. (2019), Electronic of Statistics, forthcoming. Preprint <arXiv:1611.04460>.
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2023-06-16 |
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r-fnonlinear
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Provides a collection of functions for testing various aspects of univariate time series including independence and neglected nonlinearities. Further provides functions to investigate the chaotic behavior of time series processes and to simulate different types of chaotic time series maps.
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2023-06-16 |
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r-fnn
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Cover-tree and kd-tree fast k-nearest neighbor search algorithms and related applications including KNN classification, regression and information measures are implemented.
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2023-06-16 |
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r-social
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A set of functions to quantify and visualise social autocorrelation.
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2023-06-16 |
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r-smac
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This package provides a solution path for L1-penalized angle-based classification. Three loss functions are implemented in smac, including the deviance loss in logistic regression, the exponential loss in boosting, and the proximal support vector machine loss.
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2023-06-16 |
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r-slhd
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Generate the optimal Latin Hypercube Designs (LHDs) for computer experiments with quantitative factors and the optimal Sliced Latin Hypercube Designs (SLHDs) for computer experiments with both quantitative and qualitative factors. Details of the algorithm can be found in Ba, S., Brenneman, W. A. and Myers, W. R. (2015), "Optimal Sliced Latin Hypercube Designs," Technometrics. Important function in this package is "maximinSLHD".
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2023-06-16 |
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r-simone
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Implements the inference of co-expression networks based on partial correlation coefficients from either steady-state or time-course transcriptomic data. Note that with both type of data this package can deal with samples collected in different experimental conditions and therefore not identically distributed. In this particular case, multiple but related networks are inferred on one simone run.
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2023-06-16 |
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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 is included, but if a version is already installed it will be used instead.
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2023-06-16 |
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r-rcppmlpack
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'MLPACK' is an intuitive, fast, scalable C++ machine learning library, meant to be a machine learning analog to 'LAPACK'. It aims to implement a wide array of machine learning methods and function as a Swiss army knife for machine learning researchers: 'MLPACK' is available from <http://www.mlpack.org/>; sources are included in the package.
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2023-06-16 |
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r-rbart
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A model of the form Y = f(x) + s(x) Z is fit where functions f and s are modeled with ensembles of trees and Z is standard normal. This model is developed in the paper 'Heteroscedastic BART Via Multiplicative Regression Trees' (Pratola, Chipman, George, and McCulloch, 2019, <arXiv:1709.07542v2>). BART refers to Bayesian Additive Regression Trees. See the R-package 'BART'. The predictor vector x may be high dimensional. A Markov Chain Monte Carlo (MCMC) algorithm provides Bayesian posterior uncertainty for both f and s. The MCMC uses the recent innovations in Efficient Metropolis--Hastings proposal mechanisms for Bayesian regression tree models (Pratola, 2015, Bayesian Analysis, <doi:10.1214/16-BA999>).
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2023-06-16 |
