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r-freeknotsplines
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Algorithms for fitting free-knot splines for data with one independent variable and one dependent variable. Four free-knot spline algorithms are provided for the case where the number of knots is known in advance. A knot-search algorithm is provided for the case where the number of knots is not known in advance. In addition, methods are available to compute the fitted values, the residuals, and the coefficients of the splines, and to plot the results, along with a method to summarize the results.
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2025-03-25 |
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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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2025-03-25 |
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r-fpow
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Returns the noncentrality parameter of the noncentral F distribution if probability of type I and type II error, degrees of freedom of the numerator and the denominator are given. It may be useful for computing minimal detectable differences for general ANOVA models. This program is documented in the paper of A. Baharev, S. Kemeny, On the computation of the noncentral F and noncentral beta distribution; Statistics and Computing, 2008, 18 (3), 333-340.
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2025-03-25 |
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r-fpop
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A dynamic programming algorithm for the fast segmentation of univariate signals into piecewise constant profiles. The 'fpop' package is a wrapper to a C++ implementation of the fpop (Functional Pruning Optimal Partioning) algorithm described in Maidstone et al. 2017 <doi:10.1007/s11222-016-9636-3>. The problem of detecting changepoints in an univariate sequence is formulated in terms of minimising the mean squared error over segmentations. The fpop algorithm exactly minimizes the mean squared error for a penalty linear in the number of changepoints.
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2025-03-25 |
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r-fpeek
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Tools to help text files importation. It can return the number of lines; print the first and last lines; convert encoding. Operations are made without reading the entire file before starting, resulting in good performances with large files. This package provides an alternative to a simple use of the 'head', 'tail', 'wc' and 'iconv' programs that are not always available on machine where R is installed.
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2025-03-25 |
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r-fourpno
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Estimate Barton & Lord's (1981) <doi:10.1002/j.2333-8504.1981.tb01255.x> four parameter IRT model with lower and upper asymptotes using Bayesian formulation described by Culpepper (2016) <doi:10.1007/s11336-015-9477-6>.
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2025-03-25 |
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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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2025-03-25 |
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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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2025-03-25 |
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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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2025-03-25 |
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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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2025-03-25 |
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r-fmstable
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Some basic procedures for dealing with log maximally skew stable distributions, which are also called finite moment log stable distributions.
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2025-03-25 |
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r-fmrs
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Provides parameter estimation as well as variable selection in Finite Mixture of Accelerated Failure Time Regression and Finite Mixture of Regression Models. Furthermore, this package provides Ridge Regression and Elastic Net.
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2025-03-25 |
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r-flsa
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Implements a path algorithm for the Fused Lasso Signal Approximator. For more details see the help files or the article by Hoefling (2009) <arXiv:0910.0526>.
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2025-03-25 |
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r-flock
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Implements synchronization between R processes (spawned by using the "parallel" package for instance) using file locks. Supports both exclusive and shared locking.
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2025-03-25 |
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r-float
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R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off. The internal representation is an S4 class, which allows us to keep the syntax identical to that of base R's. Interaction between floats and base types for binary operators is generally possible; in these cases, type promotion always defaults to the higher precision. The package ships with copies of the single precision 'BLAS' and 'LAPACK', which are automatically built in the event they are not available on the system.
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2025-03-25 |
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r-fllat
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Fits the Fused Lasso Latent Feature model, which is used for modeling multi-sample aCGH data to identify regions of copy number variation (CNV). Produces a set of features that describe the patterns of CNV and a set of weights that describe the composition of each sample. Also provides functions for choosing the optimal tuning parameters and the appropriate number of features, and for estimating the false discovery rate.
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2025-03-25 |
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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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2025-03-25 |
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r-flashclust
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Fast implementation of hierarchical clustering
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2025-03-25 |
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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. For more information, please refer to <https://www.jmlr.org/papers/volume16/li15a/li15a.pdf>.
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2025-03-25 |
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r-sdmtools
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This packages provides a set of tools for post processing the outcomes of species distribution modeling exercises. It includes novel methods for comparing models and tracking changes in distributions through time. It further includes methods for visualizing outcomes, selecting thresholds, calculating measures of accuracy and landscape fragmentation statistics, etc.. This package was made possible in part by financial support from the Australian Research Council & ARC Research Network for Earth System Science.
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2025-03-25 |
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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, Pantalone F, Benedetti R, and Piersimoni F (2022) <doi:10.18637/jss.v103.c02>, 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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2025-03-25 |
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r-spbayes
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Fits univariate and multivariate spatio-temporal random effects models for point-referenced data using Markov chain Monte Carlo (MCMC). Details are given in Finley, Banerjee, and Gelfand (2015) <doi:10.18637/jss.v063.i13> and Finley and Banerjee <doi:10.1016/j.envsoft.2019.104608>.
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2025-03-25 |
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r-spatstat.utils
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Contains utility functions for the 'spatstat' family of packages which may also be useful for other purposes.
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2025-03-25 |
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r-spatiotemporal
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Utilities that estimate, predict and cross-validate the spatio-temporal model developed for MESA Air.
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2025-03-25 |
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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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2025-03-25 |
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r-spatialpack
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Tools to assess the association between two spatial processes. Currently, several methodologies are implemented: A modified t-test to perform hypothesis testing about the independence between the processes, a suitable nonparametric correlation coefficient, the codispersion coefficient, and an F test for assessing the multiple correlation between one spatial process and several others. Functions for image processing and computing the spatial association between images are also provided. Functions contained in the package are intended to accompany Vallejos, R., Osorio, F., Bevilacqua, M. (2020). Spatial Relationships Between Two Georeferenced Variables: With Applications in R. Springer, Cham <doi:10.1007/978-3-030-56681-4>.
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2025-03-25 |
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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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2025-03-25 |
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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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2025-03-25 |
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r-sparsio
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Fast 'SVMlight' reader and writer. 'SVMlight' is most commonly used format for storing sparse matrices (possibly with some target variable) on disk. For additional information about 'SVMlight' format see <http://svmlight.joachims.org/>.
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2025-03-25 |
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r-sparsesvm
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Fast algorithm for fitting solution paths of sparse SVM models with lasso or elastic-net regularization.
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2025-03-25 |
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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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2025-03-25 |
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r-sparsesem
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Provides elastic net penalized maximum likelihood estimator for structural equation models (SEM). The package implements `lasso` and `elastic net` (l1/l2) penalized SEM and estimates the model parameters with an efficient block coordinate ascent algorithm that maximizes the penalized likelihood of the SEM. Hyperparameters are inferred from cross-validation (CV). A Stability Selection (STS) function is also available to provide accurate causal effect selection. The software achieves high accuracy performance through a `Network Generative Pre-trained Transformer` (Network GPT) Framework with two steps: 1) pre-trains the model to generate a complete (fully connected) graph; and 2) uses the complete graph as the initial state to fit the `elastic net` penalized SEM.
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2025-03-25 |
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r-sparsehessianfd
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Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units. See Braun, M. (2017) <doi:10.18637/jss.v082.i10>.
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2025-03-25 |
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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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2025-03-25 |
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r-spam64
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Provides the Fortran code of the R package 'spam' with 64-bit integers. Loading this package together with the R package spam enables the sparse matrix class spam to handle huge sparse matrices with more than 2^31-1 non-zero elements. Documentation is provided in Gerber, Moesinger and Furrer (2017) <doi:10.1016/j.cageo.2016.11.015>.
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2025-03-25 |
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r-spam
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Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>; see 'citation("spam")' for details.
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2025-03-25 |
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r-spacejam
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This package provides an extension of conditional independence (CIG) and directed acyclic graph (DAG) estimation to the case where conditional relationships are (non-linear) additive models.
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2025-03-25 |
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r-space
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Partial correlation estimation with joint sparse regression model
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2025-03-25 |
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r-soundexbr
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The SoundexBR package provides an algorithm for decoding names into phonetic codes, as pronounced in Portuguese. The goal is for homophones to be encoded to the same representation so that they can be matched despite minor differences in spelling. The algorithm mainly encodes consonants; a vowel will not be encoded unless it is the first letter. The soundex code resultant consists of a four digits long string composed by one letter followed by three numerical digits: the letter is the first letter of the name, and the digits encode the remaining consonants.
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2025-03-25 |
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r-soobench
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Collection of different single objective test functions useful for benchmarks and algorithm development.
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2025-03-25 |
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r-sommer
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Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.
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2025-03-25 |
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r-som
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Self-Organizing Map (with application in gene clustering).
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2025-03-25 |
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r-softrandomforest
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Performs random forests for soft decision trees for a classification problem. Current limitations are for a maximum depth of 5 resulting in 16 terminal nodes. Some data cleaning is required before input. Final graphic output requires currently requires exporting to 'Microsoft Excel' for visualization. Method based on Irsoy, Yildiz and Alpaydin (2012, ISBN: 978-4-9906441-1-6).
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2025-03-25 |
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r-softimpute
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Iterative methods for matrix completion that use nuclear-norm regularization. There are two main approaches.The one approach uses iterative soft-thresholded svds to impute the missing values. The second approach uses alternating least squares. Both have an "EM" flavor, in that at each iteration the matrix is completed with the current estimate. For large matrices there is a special sparse-matrix class named "Incomplete" that efficiently handles all computations. The package includes procedures for centering and scaling rows, columns or both, and for computing low-rank SVDs on large sparse centered matrices (i.e. principal components)
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2025-03-25 |
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r-soda
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Functions, examples and other software related to the book "Software for Data Analysis: Programming with R". See package?SoDA for an overview.
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2025-03-25 |
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r-socialnetworks
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Generates social networks using either of two approaches: using either pairwise distances or territorial area intersections.
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2025-03-25 |
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r-social
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A set of functions to quantify and visualise social autocorrelation.
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2025-03-25 |
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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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2025-03-25 |
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r-sobolsequence
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R implementation of S. Joe and F. Y. Kuo(2008) <DOI:10.1137/070709359>. The implementation is based on the data file new-joe-kuo-6.21201 <http://web.maths.unsw.edu.au/~fkuo/sobol/>.
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2025-03-25 |
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r-snnr
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Solve the problem of over-parameterization in neural networks for genomic selection. Daniel Gianola, Hayrettin OkutEmail, Kent A Weigel and Guilherme JM Rosa (2011) <doi:10.1186/1471-2156-12-87>.
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2025-03-25 |
