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r-foptions
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public |
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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-fmstable
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This package implements some basic procedures for dealing with log maximally skew stable distributions, which are also called finite moment log stable distributions.
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-flashclust
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Fast implementation of hierarchical clustering
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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, Banerjee, and Cook (2014) <doi:10.1111/2041-210X.12189>.
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2025-04-22 |
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r-spatstat.utils
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Contains utility functions for the 'spatstat' package which may also be useful for other purposes.
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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. SpatialPack gives methods to complement methodologies that are available in geoR for one spatial process.
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-sparsesem
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Sparse-aware maximum likelihood for structural equation models in inferring gene regulatory networks
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2025-04-22 |
