|
r-fkf
|
public |
This is a fast and flexible implementation of the Kalman filter, which can deal with NAs. It is entirely written in C and relies fully on linear algebra subroutines contained in BLAS and LAPACK. Due to the speed of the filter, the fitting of high-dimensional linear state space models to large datasets becomes possible. This package also contains a plot function for the visualization of the state vector and graphical diagnostics of the residuals.
|
2025-03-25 |
|
r-filehash
|
public |
Implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow 'filehash' databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets. Three different file formats for representing the database are currently available and new formats can easily be incorporated by third parties for use in the 'filehash' framework.
|
2025-03-25 |
|
r-fields
|
public |
For curve, surface and function fitting with an emphasis on splines, spatial data and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets. The splines and Kriging methods are supported by functions that can determine the smoothing parameter (nugget and sill variance) and other covariance function parameters by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to use function that also estimates the correlation scale (range parameter). A major feature is that any covariance function implemented in R and following a simple format can be used for spatial prediction. There are also many useful functions for plotting and working with spatial data as images. This package also contains an implementation of sparse matrix methods for large spatial data sets and currently requires the sparse matrix (spam) package. Use help(fields) to get started and for an overview. The fields source code is deliberately commented and provides useful explanations of numerical details as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.
|
2025-03-25 |
|
r-ffbase
|
public |
Extends the out of memory vectors of 'ff' with statistical functions and other utilities to ease their usage.
|
2025-03-25 |
|
r-ff
|
public |
The ff package provides data structures that are stored on disk but behave (almost) as if they were in RAM by transparently mapping only a section (pagesize) in main memory - the effective virtual memory consumption per ff object. ff supports R's standard atomic data types 'double', 'logical', 'raw' and 'integer' and non-standard atomic types boolean (1 bit), quad (2 bit unsigned), nibble (4 bit unsigned), byte (1 byte signed with NAs), ubyte (1 byte unsigned), short (2 byte signed with NAs), ushort (2 byte unsigned), single (4 byte float with NAs). For example 'quad' allows efficient storage of genomic data as an 'A','T','G','C' factor. The unsigned types support 'circular' arithmetic. There is also support for close-to-atomic types 'factor', 'ordered', 'POSIXct', 'Date' and custom close-to-atomic types. ff not only has native C-support for vectors, matrices and arrays with flexible dimorder (major column-order, major row-order and generalizations for arrays). There is also a ffdf class not unlike data.frames and import/export filters for csv files. ff objects store raw data in binary flat files in native encoding, and complement this with metadata stored in R as physical and virtual attributes. ff objects have well-defined hybrid copying semantics, which gives rise to certain performance improvements through virtualization. ff objects can be stored and reopened across R sessions. ff files can be shared by multiple ff R objects (using different data en/de-coding schemes) in the same process or from multiple R processes to exploit parallelism. A wide choice of finalizer options allows to work with 'permanent' files as well as creating/removing 'temporary' ff files completely transparent to the user. On certain OS/Filesystem combinations, creating the ff files works without notable delay thanks to using sparse file allocation. Several access optimization techniques such as Hybrid Index Preprocessing and Virtualization are implemented to achieve good performance even with large datasets, for example virtual matrix transpose without touching a single byte on disk. Further, to reduce disk I/O, 'logicals' and non-standard data types get stored native and compact on binary flat files i.e. logicals take up exactly 2 bits to represent TRUE, FALSE and NA. Beyond basic access functions, the ff package also provides compatibility functions that facilitate writing code for ff and ram objects and support for batch processing on ff objects (e.g. as.ram, as.ff, ffapply). ff interfaces closely with functionality from package 'bit': chunked looping, fast bit operations and coercions between different objects that can store subscript information ('bit', 'bitwhich', ff 'boolean', ri range index, hi hybrid index). This allows to work interactively with selections of large datasets and quickly modify selection criteria. Further high-performance enhancements can be made available upon request.
|
2025-03-25 |
|
r-fastmatch
|
public |
Package providing a fast match() replacement for cases that require repeated look-ups. It is slightly faster that R's built-in match() function on first match against a table, but extremely fast on any subsequent lookup as it keeps the hash table in memory.
|
2025-03-25 |
|
r-fastica
|
public |
Implementation of FastICA algorithm to perform Independent Component Analysis (ICA) and Projection Pursuit.
|
2025-03-25 |
|
r-fastghquad
|
public |
Fast, numerically-stable Gauss-Hermite quadrature rules and utility functions for adaptive GH quadrature. See Liu, Q. and Pierce, D. A. (1994) <doi:10.2307/2337136> for a reference on these methods.
|
2025-03-25 |
|
r-farver
|
public |
The encoding of colour can be handled in many different ways, using different colour spaces. As different colour spaces have different uses, efficient conversion between these representations are important. The 'farver' package provides a set of functions that gives access to very fast colour space conversion and comparisons implemented in C++, and offers 100-fold speed improvements over the 'convertColor' function in the 'grDevices' package.
|
2025-03-25 |
|
r-fansi
|
public |
Counterparts to R string manipulation functions that account for the effects of ANSI text formatting control sequences.
|
2025-03-25 |
|
r-expm
|
public |
Computation of the matrix exponential, logarithm, sqrt, and related quantities.
|
2025-03-25 |
|
r-expint
|
public |
The exponential integrals E_1(x), E_2(x), E_n(x) and Ei(x), and the incomplete gamma function G(a, x) defined for negative values of its first argument. The package also gives easy access to the underlying C routines through an API; see the package vignette for details. A test package included in sub-directory example_API provides an implementation. C routines derived from the GNU Scientific Library <https://www.gnu.org/software/gsl/>.
|
2025-03-25 |
|
r-evd
|
public |
Extends simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models.
|
2025-03-25 |
|
r-energy
|
public |
E-statistics (energy) tests and statistics for multivariate and univariate inference, including distance correlation, one-sample, two-sample, and multi-sample tests for comparing multivariate distributions, are implemented. Measuring and testing multivariate independence based on distance correlation, partial distance correlation, multivariate goodness-of-fit tests, k-groups and hierarchical clustering based on energy distance, testing for multivariate normality, distance components (disco) for non-parametric analysis of structured data, and other energy statistics/methods are implemented.
|
2025-03-25 |
|
r-emmixskew
|
public |
EM algorithm for Fitting Mixture of Multivariate Skew Normal and Skew t Distributions. An implementation of the algorithm described in Wang, Ng, and McLachlan (2009) <doi:10.1109/DICTA.2009.88>.
|
2025-03-25 |
|
r-ellipsis
|
public |
In S3 generics, it's useful to take ... so that methods can have additional argument. But this flexibility comes at a cost: misspelled arguments will be silently ignored. The ellipsis packages is an experiment that allows a generic to warn if any arguments passed in ... are not used.
|
2025-03-25 |
|
r-earth
|
public |
Build regression models using the techniques in Friedman's papers "Fast MARS" and "Multivariate Adaptive Regression Splines" <doi:10.1214/aos/1176347963>. (The term "MARS" is trademarked and thus not used in the name of the package.)
|
2025-03-25 |
|
r-e1071
|
public |
Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, ...
|
2025-03-25 |
|
r-dtw
|
public |
A comprehensive implementation of dynamic time warping (DTW) algorithms in R. DTW computes the optimal (least cumulative distance) alignment between points of two time series. Common DTW variants covered include local (slope) and global (window) constraints, subsequence matches, arbitrary distance definitions, normalizations, minimum variance matching, and so on. Provides cumulative distances, alignments, specialized plot styles, etc.
|
2025-03-25 |
|
r-dse
|
public |
Tools for multivariate, linear, time-invariant, time series models. This includes ARMA and state-space representations, and methods for converting between them. It also includes simulation methods and several estimation functions. The package has functions for looking at model roots, stability, and forecasts at different horizons. The ARMA model representation is general, so that VAR, VARX, ARIMA, ARMAX, ARIMAX can all be considered to be special cases. Kalman filter and smoother estimates can be obtained from the state space model, and state-space model reduction techniques are implemented. An introduction and User's Guide is available in a vignette.
|
2025-03-25 |
|
r-dotcall64
|
public |
Provides .C64(), which is an enhanced version of .C() and .Fortran() from the foreign function interface. .C64() supports long vectors, arguments of type 64-bit integer, and provides a mechanism to avoid unnecessary copies of read-only and write-only arguments. This makes it a convenient and fast interface to C/C++ and Fortran code.
|
2025-03-25 |
|
r-dlm
|
public |
Provides routines for Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear Models.
|
2025-03-25 |
|
r-distributionutils
|
public |
Utilities are provided which are of use in the packages I have developed for dealing with distributions. Currently these packages are GeneralizedHyperbolic, VarianceGamma, and SkewHyperbolic and NormalLaplace. Each of these packages requires DistributionUtils. Functionality includes sample skewness and kurtosis, log-histogram, tail plots, moments by integration, changing the point about which a moment is calculated, functions for testing distributions using inversion tests and the Massart inequality. Also includes an implementation of the incomplete Bessel K function.
|
2025-03-25 |
|
r-diptest
|
public |
Compute Hartigan's dip test statistic for unimodality / multimodality and provide a test with simulation based p-values, where the original public code has been corrected.
|
2025-03-25 |
|
r-digest
|
public |
Implementation of a function 'digest()' for the creation of hash digests of arbitrary R objects (using the 'md5', 'sha-1', 'sha-256', 'crc32', 'xxhash', 'murmurhash' and 'spookyhash' algorithms) permitting easy comparison of R language objects, as well as functions such as'hmac()' to create hash-based message authentication code. Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as 'OpenSSL' should be used.
|
2025-03-25 |
|
r-diffobj
|
public |
Generate a colorized diff of two R objects for an intuitive visualization of their differences.
|
2025-03-25 |
|
r-devemf
|
public |
Output graphics to EMF+/EMF.
|
2025-03-25 |
|
r-desolve
|
public |
Functions that solve initial value problems of a system of first-order ordinary differential equations ('ODE'), of partial differential equations ('PDE'), of differential algebraic equations ('DAE'), and of delay differential equations. The functions provide an interface to the FORTRAN functions 'lsoda', 'lsodar', 'lsode', 'lsodes' of the 'ODEPACK' collection, to the FORTRAN functions 'dvode', 'zvode' and 'daspk' and a C-implementation of solvers of the 'Runge-Kutta' family with fixed or variable time steps. The package contains routines designed for solving 'ODEs' resulting from 1-D, 2-D and 3-D partial differential equations ('PDE') that have been converted to 'ODEs' by numerical differencing.
|
2025-03-25 |
|
r-descr
|
public |
Weighted frequency and contingency tables of categorical variables and of the comparison of the mean value of a numerical variable by the levels of a factor, and methods to produce xtable objects of the tables and to plot them. There are also functions to facilitate the character encoding conversion of objects, to quickly convert fixed width files into csv ones, and to export a data.frame to a text file with the necessary R and SPSS codes to reread the data.
|
2025-03-25 |
|
r-deldir
|
public |
Calculates the Delaunay triangulation and the Dirichlet or Voronoi tessellation (with respect to the entire plane) of a planar point set. Plots triangulations and tessellations in various ways. Clips tessellations to sub-windows. Calculates perimeters of tessellations. Summarises information about the tiles of the tessellation.
|
2025-03-25 |
|
r-dcurver
|
public |
A Davidian curve defines a seminonparametric density, whose shape and flexibility can be tuned by easy to estimate parameters. Since a special case of a Davidian curve is the standard normal density, Davidian curves can be used for relaxing normality assumption in statistical applications (Zhang & Davidian, 2001) <doi:10.1111/j.0006-341X.2001.00795.x>. This package provides the density function, the gradient of the loglikelihood and a random generator for Davidian curves.
|
2025-03-25 |
|
r-dbscan
|
public |
A fast reimplementation of several density-based algorithms of the DBSCAN family for spatial data. Includes the DBSCAN (density-based spatial clustering of applications with noise) and OPTICS (ordering points to identify the clustering structure) clustering algorithms HDBSCAN (hierarchical DBSCAN) and the LOF (local outlier factor) algorithm. The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided.
|
2025-03-25 |
|
r-date
|
public |
Functions for handling dates.
|
2025-03-25 |
|
r-data.table
|
public |
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
|
2025-03-25 |
|
r-curl
|
public |
The curl() and curl_download() functions provide highly configurable drop-in replacements for base url() and download.file() with better performance, support for encryption (https, ftps), gzip compression, authentication, and other 'libcurl' goodies. The core of the package implements a framework for performing fully customized requests where data can be processed either in memory, on disk, or streaming via the callback or connection interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly web client see the 'httr' package which builds on this package with http specific tools and logic.
|
2025-03-25 |
|
r-cubature
|
public |
R wrappers around the cubature C library of Steven G. Johnson for adaptive multivariate integration over hypercubes and the Cuba C library of Thomas Hahn for deterministic and Monte Carlo integration. Scalar and vector interfaces for cubature and Cuba routines are provided; the vector interfaces are highly recommended as demonstrated in the package vignette.
|
2025-03-25 |
|
r-coranking
|
public |
Calculates the co-ranking matrix to assess the quality of a dimensionality reduction.
|
2025-03-25 |
|
r-contfrac
|
public |
Various utilities for evaluating continued fractions.
|
2025-03-25 |
|
r-coneproj
|
public |
Routines doing cone projection and quadratic programming, as well as doing estimation and inference for constrained parametric regression and shape-restricted regression problems. See Mary C. Meyer (2013)<doi:10.1080/03610918.2012.659820> for more details.
|
2025-03-25 |
|
r-compquadform
|
public |
Computes the distribution function of quadratic forms in normal variables using Imhof's method, Davies's algorithm, Farebrother's algorithm or Liu et al.'s algorithm.
|
2025-03-25 |
|
r-commonmark
|
public |
The CommonMark specification defines a rationalized version of markdown syntax. This package uses the 'cmark' reference implementation for converting markdown text into various formats including html, latex and groff man. In addition it exposes the markdown parse tree in xml format. Also includes opt-in support for GFM extensions including tables, autolinks, and strikethrough text.
|
2025-03-25 |
|
r-colorspace
|
public |
Carries out mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB and polar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided along with corresponding ggplot2 color scales. Color palette choice is aided by an interactive app (with either a Tcl/Tk or a shiny GUI) and shiny apps with an HCL color picker and a color vision deficiency emulator. Plotting functions for displaying and assessing palettes include color swatches, visualizations of the HCL space, and trajectories in HCL and/or RGB spectrum. Color manipulation functions include: desaturation, lightening/darkening, mixing, and simulation of color vision deficiencies (deutanomaly, protanomaly, tritanomaly).
|
2025-03-25 |
|
r-clv
|
public |
Package contains most of the popular internal and external cluster validation methods ready to use for the most of the outputs produced by functions coming from package "cluster". Package contains also functions and examples of usage for cluster stability approach that might be applied to algorithms implemented in "cluster" package as well as user defined clustering algorithms.
|
2025-03-25 |
|
r-cluster
|
public |
Methods for Cluster analysis. Much extended the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) "Finding Groups in Data".
|
2025-03-25 |
|
r-clue
|
public |
CLUster Ensembles.
|
2025-03-25 |
|
r-class
|
public |
Various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps.
|
2025-03-25 |
|
r-ckmeans.1d.dp
|
public |
Fast optimal univariate clustering and segementation by dynamic programming. Three types of problem including univariate k-means, k-median, and k-segments are solved with guaranteed optimality and reproducibility. The core algorithm minimizes the sum of within-cluster distances using respective metrics. Its advantage over heuristic clustering algorithms in efficiency and accuracy is increasingly pronounced as the number of clusters k increases. Weighted k-means and unweighted k-segments algorithms can also optimally segment time series and perform peak calling. An auxiliary function generates histograms that are adaptive to patterns in data. In contrast to heuristic methods, this package provides a powerful set of tools for univariate data analysis with guaranteed optimality. Use four spaces when indenting paragraphs within the Description.
|
2025-03-25 |
|
r-chron
|
public |
Provides chronological objects which can handle dates and times.
|
2025-03-25 |
|
r-checkmate
|
public |
Tests and assertions to perform frequent argument checks. A substantial part of the package was written in C to minimize any worries about execution time overhead.
|
2025-03-25 |
|
r-changepoint
|
public |
Implements various mainstream and specialised changepoint methods for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included. The cpt.mean(), cpt.var(), cpt.meanvar() functions should be your first point of call.
|
2025-03-25 |
