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r-shiftr
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Fast enrichment analysis for locally correlated statistics via circular permutations. The analysis can be performed at multiple significance thresholds for both primary and auxiliary data sets with efficient correction for multiple testing.
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2023-06-16 |
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r-sgloptim
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Fast generic solver for sparse group lasso optimization problems. The loss (objective) function must be defined in a C++ module. The optimization problem is solved using a coordinate gradient descent algorithm. Convergence of the algorithm is established (see reference) and the algorithm is applicable to a broad class of loss functions. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.
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2023-06-16 |
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r-sgeostat
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An Object-oriented Framework for Geostatistical Modeling in S+ containing functions for variogram estimation, variogram fitting and kriging as well as some plot functions. Written entirely in S, therefore works only for small data sets in acceptable computing time.
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2023-06-16 |
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r-secr
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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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2023-06-16 |
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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 <http://rapidxml.sourceforge.net> is used to parse the XML data.
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2023-06-16 |
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r-rarcinfo
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This package uses the functions written by Daniel Morissette <[email protected]> to read geographical information in Arc/Info V 7.x format and E00 files to import the coverages into R variables.
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2023-06-16 |
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r-qtlmt
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Provides tools for joint analysis of multiple traits in a backcross (BC) or recombinant inbred lines (RIL) population. It can be used to select an optimal subset of traits for multiple-trait mapping, analyze multiple traits via the SURE model, which can associate different QTL with different traits, and perform multiple-trait composite multiple-interval mapping.
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2023-06-16 |
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r-genodds
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Calculates Agresti's (1980) <https://www.jstor.org/stable/2530495> generalized odds ratios. For a randomly selected pair of observations from two groups, calculates the odds that the second group will have a higher scoring outcome than that of the first group. Package provides hypothesis testing for if this odds ratio is significantly different to 1 (equal chance).
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2023-06-16 |
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r-galgo
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Build multivariate predictive models from large datasets having far larger number of features than samples such as in functional genomics datasets. Trevino and Falciani (2006) <doi:10.1093/bioinformatics/btl074>.
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2023-06-16 |
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r-fselectorrcpp
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'Rcpp' (free of 'Java'/'Weka') implementation of 'FSelector' entropy-based feature selection algorithms based on an MDL discretization (Fayyad U. M., Irani K. B.: Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. In 13'th International Joint Conference on Uncertainly in Artificial Intelligence (IJCAI93), pages 1022-1029, Chambery, France, 1993.) <https://www.ijcai.org/Proceedings/93-2/Papers/022.pdf> with a sparse matrix support. It is also equipped with a parallel backend.
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2023-06-16 |
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r-sparsesvd
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Wrapper around the 'SVDLIBC' library for (truncated) singular value decomposition of a sparse matrix. Currently, only sparse real matrices in Matrix package format are supported.
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2023-06-16 |
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r-snipem
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Snipping methods optimally removing scattered cells for robust estimation and cluster analysis.
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2023-06-16 |
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r-skda
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Sparse (Multicategory) Kernel Discriminant Analysis does variable selection for nonparametric classification
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2023-06-16 |
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r-simframe
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A general framework for statistical simulation.
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2023-06-16 |
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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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2023-06-16 |
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r-r4dfp
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This package provides an R interface with 2-part 4dfp MRI images (.4dfp.ifh and .4dfp.img files.)
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2023-06-16 |
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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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2023-06-16 |
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r-rcppcnpy
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The 'cnpy' library written by Carl Rogers provides read and write facilities for files created with (or for) the 'NumPy' extension for 'Python'. Vectors and matrices of numeric types can be read or written to and from files as well as compressed files. Support for integer files is available if the package has been built with -std=c++11 which should be the default on all platforms since the release of R 3.3.0.
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2023-06-16 |
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r-rbacon
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Bacon is an approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for deposits, through combining radiocarbon and other dates with prior information. See Blaauw & Christen (2011) <doi:10.1214/11-BA618>.
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2023-06-16 |
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r-rarhsmm
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Fit Gaussian hidden Markov (or semi-Markov) models with / without autoregressive coefficients and with / without regularization. The fitting algorithm for the hidden Markov model is illustrated by Rabiner (1989) <doi:10.1109/5.18626>. The shrinkage estimation on the covariance matrices is based on the method by Ledoit et al. (2004) <doi:10.1016/S0047-259X(03)00096-4>. The shrinkage estimation on the autoregressive coefficients uses the elastic net shrinkage detailed in Zou et al. (2005) <doi:10.1111/j.1467-9868.2005.00503.x>.
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2023-06-16 |
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r-glmlep
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Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by LEP.
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2023-06-16 |
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r-ghyp
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Detailed functionality for working with the univariate and multivariate Generalized Hyperbolic distribution and its special cases (Hyperbolic (hyp), Normal Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t and Gaussian distribution). Especially, it contains fitting procedures, an AIC-based model selection routine, and functions for the computation of density, quantile, probability, random variates, expected shortfall and some portfolio optimization and plotting routines as well as the likelihood ratio test. In addition, it contains the Generalized Inverse Gaussian distribution.
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2023-06-16 |
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r-gforce
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A complete suite of computationally efficient methods for high dimensional clustering and inference problems in G-Latent Models (a type of Latent Variable Gaussian graphical model). The main feature is the FORCE (First-Order, Certifiable, Efficient) clustering algorithm which is a fast solver for a semi-definite programming (SDP) relaxation of the K-means problem. For certain types of graphical models (G-Latent Models), with high probability the algorithm not only finds the optimal clustering, but produces a certificate of having done so. This certificate, however, is model independent and so can also be used to certify data clustering problems. The 'GFORCE' package also contains implementations of inferential procedures for G-Latent graphical models using n-fold cross validation. Also included are native code implementations of other popular clustering methods such as Lloyd's algorithm with kmeans++ initialization and complete linkage hierarchical clustering. The FORCE method is due to Eisenach and Liu (2019) <arxiv:1806.00530>.
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2023-06-16 |
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r-gettz
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A function to retrieve the system timezone on Unix systems which has been found to find an answer when 'Sys.timezone()' has failed. It is based on an answer by Duane McCully posted on 'StackOverflow', and adapted to be callable from R. The package also builds on Windows, but just returns NULL.
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2023-06-16 |
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r-geoops
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Tools for doing calculations and manipulations on 'GeoJSON', a 'geospatial' data interchange format (<https://tools.ietf.org/html/rfc7946>). 'GeoJSON' is also valid 'JSON'.
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2023-06-16 |
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r-gb
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A collection of algorithms and functions for fitting data to a generalized lambda distribution via moment matching methods, and generalized bootstrapping.
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2023-06-16 |
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r-fwsim
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Simulates a population under the Fisher-Wright model (fixed or stochastic population size) with a one-step neutral mutation process (stepwise mutation model, logistic mutation model and exponential mutation model supported). The stochastic population sizes are random Poisson distributed and different kinds of population growth are supported. For the stepwise mutation model, it is possible to specify locus and direction specific mutation rate (in terms of upwards and downwards mutation rate). Intermediate generations can be saved in order to study e.g. drift.
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2023-06-16 |
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r-space
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Partial correlation estimation with joint sparse regression model
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2023-06-16 |
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r-sitmo
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Provided within are two high quality and fast PPRNGs that may be used in an 'OpenMP' parallel environment. In addition, there is a generator for one dimensional low-discrepancy sequence. The objective of this library to consolidate the distribution of the 'sitmo' (C++98 & C++11), 'threefry' and 'vandercorput' (C++11-only) engines on CRAN by enabling others to link to the header files inside of 'sitmo' instead of including a copy of each engine within their individual package. Lastly, the package contains example implementations using the 'sitmo' package and three accompanying vignette that provide additional information.
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2023-06-16 |
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r-simputation
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Easy to use interfaces to a number of imputation methods that fit in the not-a-pipe operator of the 'magrittr' package.
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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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' 8.400 or later.
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2023-06-16 |
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r-rcppcctz
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'Rcpp' Access to the 'CCTZ' timezone library is provided. 'CCTZ' is a C++ library for translating between absolute and civil times using the rules of a time zone. The 'CCTZ' source code, released under the Apache 2.0 License, is included in this package. See <https://github.com/google/cctz> for more details.
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2023-06-16 |
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r-ramsvm
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Provides a solution path for Reinforced Angle-based Multicategory Support Vector Machines, with linear learning, polynomial learning, and Gaussian kernel learning.
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2023-06-16 |
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r-qpot
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Tools to 1) simulate and visualize stochastic differential equations and 2) determine stability of equilibria using the ordered-upwind method to compute the quasi-potential.
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2023-06-16 |
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r-pweall
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Calculates various functions needed for design and monitoring survival trials accounting for complex situations such as delayed treatment effect, treatment crossover, non-uniform accrual, and different censoring distributions between groups. The event time distribution is assumed to be piecewise exponential (PWE) distribution and the entry time is assumed to be piecewise uniform distribution. As compared with Version 1.2.1, two more types of hybrid crossover are added. A bug is corrected in the function "pwecx" that calculates the crossover-adjusted survival, distribution, density, hazard and cumulative hazard functions. Also, to generate the crossover-adjusted event time random variable, a more efficient algorithm is used and the output includes crossover indicators.
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2023-06-16 |
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r-pwd
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Contains functions which allow the user to perform time series regression quickly using the Power Weighted Densities (PWD) approach. alphahat_LR_one_Rcpp() is the main workhorse function within this package.
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2023-06-16 |
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r-glm.deploy
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Provides two functions that generate source code implementing the predict function of fitted glm objects. In this version, code can be generated for either 'C' or 'Java'. The idea is to provide a tool for the easy and fast deployment of glm predictive models into production. The source code generated by this package implements two function/methods. One of such functions implements the equivalent to predict(type="response"), while the second implements predict(type="link"). Source code is written to disk as a .c or .java file in the specified path. In the case of c, an .h file is also generated.
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2023-06-16 |
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r-glide
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Functions evaluate global and individual tests for direct effects in Mendelian randomization studies.
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2023-06-16 |
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r-gldex
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The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution.
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2023-06-16 |
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r-glasso
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Estimation of a sparse inverse covariance matrix using a lasso (L1) penalty. Facilities are provided for estimates along a path of values for the regularization parameter.
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2023-06-16 |
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r-gamesga
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Finds adaptive strategies for sequential symmetric games using a genetic algorithm. Currently, any symmetric two by two matrix is allowed, and strategies can remember the history of an opponent's play from the previous three rounds of moves in iterated interactions between players. The genetic algorithm returns a list of adaptive strategies given payoffs, and the mean fitness of strategies in each generation.
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2023-06-16 |
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r-fourierin
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Computes Fourier integrals of functions of one and two variables using the Fast Fourier transform. The Fourier transforms must be evaluated on a regular grid for fast evaluation.
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2023-06-16 |
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r-flare
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Provide the implementation of a family of Lasso variants including Dantzig Selector, LAD Lasso, SQRT Lasso, Lq Lasso for estimating high dimensional sparse linear model. We adopt the alternating direction method of multipliers and convert the original optimization problem into a sequential L1 penalized least square minimization problem, which can be efficiently solved by linearization algorithm. A multi-stage screening approach is adopted for further acceleration. Besides the sparse linear model estimation, we also provide the extension of these Lasso variants to sparse Gaussian graphical model estimation including TIGER and CLIME using either L1 or adaptive penalty. Missing values can be tolerated for Dantzig selector and CLIME. The computation is memory-optimized using the sparse matrix output.
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2023-06-16 |
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r-spbsampling
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Selection of spatially balanced samples. In particular, the implemented sampling designs allow to select probability samples well spread over the population of interest, in any dimension and using any distance function (e.g. Euclidean distance, Manhattan distance). For more details, Benedetti R and Piersimoni F (2017) <doi:10.1002/bimj.201600194> and Benedetti R and Piersimoni F (2017) <arXiv:1710.09116>. The implementation has been done in C++ through the use of 'Rcpp' and 'RcppArmadillo'.
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2023-06-16 |
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r-spatimeclus
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Mixture model is used to achieve the clustering goal. Each component is itself a mixture model of polynomial autoregressive regressions whose the logistic weights consider the spatial and temporal information.
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2023-06-16 |
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r-spatialnp
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Test and estimates of location, tests of independence, tests of sphericity and several estimates of shape all based on spatial signs, symmetrized signs, ranks and signed ranks. For details, see Oja and Randles (2004) <doi:10.1214/088342304000000558> and Oja (2010) <doi:10.1007/978-1-4419-0468-3>.
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2023-06-16 |
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r-soccer
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Functions for evaluating tournament predictions, simulating results from individual soccer matches and tournaments. See <http://sandsynligvis.dk/2018/08/03/world-cup-prediction-winners/> for more information.
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2023-06-16 |
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r-snakecharmr
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Run 'Python' code, make function calls, assign and retrieve variables, etc. from R. A fork from 'rPython' which uses 'jsonlite', 'Rcpp' and has several fixes and improvements.
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2023-06-16 |
