Packages — R (Page 4 of 11)
r-hexbin 1.27.2 — Hexagonal binning routines
This package provides binning and plotting functions for hexagonal bins. It uses and relies on grid graphics and formal (S4) classes and methods.
r-highr 0.7 — Syntax highlighting for R source code
This package provides syntax highlighting for R source code. Currently it supports LaTeX and HTML output. Source code of other languages is supported via Andre Simon's highlight package.
r-hitc 1.24.0 — High throughput chromosome conformation capture analysis
The HiTC package was developed to explore high-throughput "C" data such as 5C or Hi-C. Dedicated R classes as well as standard methods for quality controls, normalization, visualization, and further analysis are also provided.
r-hmisc 4.1-1 — Miscellaneous data analysis and graphics functions
This package contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX code, and recoding variables.
r-hms 0.4.2 — Pretty time of day
This package implements an S3 class for storing and formatting time-of-day values, based on the
r-homo-sapiens 1.3.1 — Annotation package for the Homo.sapiens object
This package contains the Homo.sapiens object to access data from several related annotation packages.
r-hpar 1.22.2 — Human Protein Atlas in R
This package provides a simple interface to and data from the Human Protein Atlas project.
r-htmltable 1.12 — Advanced tables for Markdown/HTML
This package provides functions to build tables with advanced layout elements such as row spanners, column spanners, table spanners, zebra striping, and more. While allowing advanced layout, the underlying CSS-structure is simple in order to maximize compatibility with word processors such as LibreOffice. The package also contains a few text formatting functions that help outputting text compatible with HTML or LaTeX.
r-htmltools 0.3.6 — R tools for HTML
This package provides tools for HTML generation and output in R.
r-htmlwidgets 1.2 — HTML Widgets for R
HTML widgets is a framework for creating HTML widgets that render in various contexts including the R console, R Markdown documents, and Shiny web applications.
r-httpuv 1.4.5 — HTTP and WebSocket server library for R
The httpuv package provides low-level socket and protocol support for handling HTTP and WebSocket requests directly from within R. It is primarily intended as a building block for other packages, rather than making it particularly easy to create complete web applications using httpuv alone.
r-httr 1.3.1 — Tools for working with URLs and HTTP
The aim of httr is to provide a wrapper for RCurl customised to the demands of modern web APIs. It provides useful tools for working with HTTP organised by HTTP verbs (
POST(), etc). Configuration functions make it easy to control additional request components.
r-hwriter 1.3.2 — Output R objects in HTML format
This package provides easy-to-use and versatile functions to output R objects in HTML format.
r-ica 1.0-2 — Independent component analysis
This package provides tools for Independent Component Analysis (ICA) using various algorithms: FastICA, Information-Maximization (Infomax), and Joint Approximate Diagonalization of Eigenmatrices (JADE).
r-idr 1.2 — Irreproducible discovery rate
This is a package for estimating the copula mixture model and plotting correspondence curves in "Measuring reproducibility of high-throughput experiments" (2011), Annals of Applied Statistics, Vol. 5, No. 3, 1752-1779, by Li, Brown, Huang, and Bickel
r-ifultools 2.0-4 — Insightful research tools
This package provides C code used by the wmtsa, fractal, and sapa R packages.
r-igraph 1.2.2 — Network analysis and visualization
This package provides routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.
r-import 1.1.0 — Import mechanism for R
This is an alternative mechanism for importing objects from packages. The syntax allows for importing multiple objects from a package with a single command in an expressive way. The import package bridges some of the gap between using
require) and direct (single-object) imports. Furthermore the imported objects are not placed in the current environment. It is also possible to import objects from stand-alone
r-impute 1.54.0 — Imputation for microarray data
This package provides a function to impute missing gene expression microarray data, using nearest neighbor averaging.
r-infotheo 1.2.0 — Information-theoretic measures
This package implements various measures of information theory based on several entropy estimators.
r-inline 0.3.15 — Functions to inline C, C++, Fortran function calls from R
This package provides functionality to dynamically define R functions and S4 methods with inlined C, C++ or Fortran code supporting
.Call calling conventions.
r-inspect 1.10.0 — Analysis of 4sU-seq and RNA-seq time-course data
INSPEcT (INference of Synthesis, Processing and dEgradation rates in Time-Course experiments) analyses 4sU-seq and RNA-seq time-course data in order to evaluate synthesis, processing and degradation rates and assess via modeling the rates that determines changes in mature mRNA levels.
r-interactionset 1.8.0 — Base classes for storing genomic interaction data
This packages provides the
ContactMatrix objects and associated methods for storing and manipulating genomic interaction data from Hi-C and ChIA-PET experiments.
r-interactivedisplaybase 1.18.0 — Base package for web displays of Bioconductor objects
This package contains the basic methods needed to generate interactive Shiny-based display methods for Bioconductor objects.
r-ipred 0.9-7 — Improved predictors
This package provides improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.
r-iranges 2.14.11 — Infrastructure for manipulating intervals on sequences
This package provides efficient low-level and highly reusable S4 classes for storing ranges of integers, RLE vectors (Run-Length Encoding), and, more generally, data that can be organized sequentially (formally defined as
Vector objects), as well as views on these
Vector objects. Efficient list-like classes are also provided for storing big collections of instances of the basic classes. All classes in the package use consistent naming and share the same rich and consistent "Vector API" as much as possible.
r-irlba 2.3.2 — Methods for eigendecomposition of large matrices
This package provides fast and memory efficient methods for truncated singular and eigenvalue decompositions, as well as for principal component analysis of large sparse or dense matrices.
r-iterators 1.0.10 — Iterator construct for R
This package provides support for iterators, which allow a programmer to traverse through all the elements of a vector, list, or other collection of data.
r-itertools 0.1-3 — Iterator tools
This package provides various tools for creating iterators, many patterned after functions in the Python
itertools module, and others patterned after functions in the snow package.
r-jomo 2.6-4 — Multilevel Joint Modelling Multiple Imputation
Similarly to Schafer's package pan, jomo is a package for multilevel joint modelling multiple imputation http://doi.org/10.1002/9781119942283. Novel aspects of jomo are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.
r-jpeg 0.1-8 — Read and write JPEG images with R
This package provides a way to read, write and display bitmap images stored in the JPEG format with R. It can read and write both files and in-memory raw vectors.
r-jsonlite 1.5 — Robust, high performance JSON parser and generator for R
The jsonlite package provides a fast JSON parser and generator optimized for statistical data and the web. It offers flexible, robust, high performance tools for working with JSON in R and is particularly powerful for building pipelines and interacting with a web API. In addition to converting JSON data from/to R objects, jsonlite contains functions to stream, validate, and prettify JSON data. The unit tests included with the package verify that all edge cases are encoded and decoded consistently for use with dynamic data in systems and applications.
r-keggrest 1.20.1 — Client-side REST access to KEGG
This package provides a package that provides a client interface to the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST server.
r-kernlab 0.9-27 — Kernel-based machine learning tools
This package provides kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods
kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.
r-kernsmooth 2.23-15 — Functions for kernel smoothing
This package provides functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing".
r-knitr 1.20 — General-purpose package for dynamic report generation in R
This package provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.
r-knitrbootstrap 1.0.2 — Knitr bootstrap framework
This package provides a framework to create Bootstrap 3 HTML reports from knitr Rmarkdown.
r-ksamples 1.2-8 — K-Sample rank tests and their combinations
This package provides tools to compares k samples using the Anderson-Darling test, Kruskal-Wallis type tests with different rank score criteria, Steel's multiple comparison test, and the Jonckheere-Terpstra (JT) test. It computes asymptotic, simulated or (limited) exact P-values, all valid under randomization, with or without ties, or conditionally under random sampling from populations, given the observed tie pattern. Except for Steel's test and the JT test it also combines these tests across several blocks of samples.
r-labeling 0.3 — Axis labeling algorithms
The labeling package provides a range of axis labeling algorithms.
r-laeken 0.4.6 — Estimation of indicators on social exclusion and poverty
This package provides tools for the estimation of indicators on social exclusion and poverty, as well as an implementation of Pareto tail modeling for empirical income distributions.
r-lambda-r 1.2.3 — Functional programming extension for R
This package provides a language extension to efficiently write functional programs in R. Syntax extensions include multi-part function definitions, pattern matching, guard statements, built-in (optional) type safety.
r-lars 1.2 — Least angle regression software
Least Angle Regression ("LAR") is a model selection algorithm; a useful and less greedy version of traditional forward selection methods. A simple modification of the LAR algorithm implements Tibshirani's Lasso; the Lasso modification of LARS calculates the entire Lasso path of coefficients for a given problem at the cost of a single least squares fit. Another LARS modification efficiently implements epsilon Forward Stagewise linear regression.
r-later 0.7.4 — Utilities for delaying function execution
This package provides tools to execute arbitrary R or C functions some time after the current time, after the R execution stack has emptied.
r-lattice 0.20-35 — High-level data visualization system
The lattice package provides a powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements.
r-latticeextra 0.6-28 — Extra graphical utilities based on lattice
Building on the infrastructure provided by the lattice package, this package provides several new high-level graphics functions and methods, as well as additional utilities such as panel and axis annotation functions.
r-lava 1.6.3 — Latent variable models
This package provides tools for the estimation and simulation of latent variable models.
r-lazyeval 0.2.1 — Lazy (non-standard) evaluation in R
This package provides the tools necessary to do non-standard evaluation (NSE) in R.
r-ldblock 1.10.0 — Data structures for linkage disequilibrium measures in populations
This package defines data structures for linkage disequilibrium (LD) measures in populations. Its purpose is to simplify handling of existing population-level data for the purpose of flexibly defining LD blocks.
r-leaps 3.0 — Regression subset selection
This package provides tools for regression subset selection, including exhaustive search.
r-learnr 0.9.2.1 — Interactive tutorials for R
This package provides tools to create interactive tutorials using R Markdown. Use a combination of narrative, figures, videos, exercises, and quizzes to create self-paced tutorials for learning about R and R packages.
r-limma 3.36.3 — Package for linear models for microarray and RNA-seq data
This package can be used for the analysis of gene expression studies, especially the use of linear models for analysing designed experiments and the assessment of differential expression. The analysis methods apply to different technologies, including microarrays, RNA-seq, and quantitative PCR.
r-limsolve 22.214.171.124 — Solving linear inverse models
This package provides functions that:
find the minimum/maximum of a linear or quadratic function,
sample an underdetermined or overdetermined system,
solve a linear system Ax=B for the unknown x.
It includes banded and tridiagonal linear systems. The package calls Fortran functions from LINPACK.
r-lme4 1.1-18-1 — Linear mixed-effects models using eigen and S4
This package provides fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the Eigen C++ library for numerical linear algebra and RcppEigen glue.
r-lmoments 1.2-3 — L-moments and quantile mixtures
This package contains functions to estimate L-moments and trimmed L-moments from the data. It also contains functions to estimate the parameters of the normal polynomial quantile mixture and the Cauchy polynomial quantile mixture from L-moments and trimmed L-moments.
r-lmtest 0.9-36 — Testing linear regression models
This package provides a collection of tests, data sets, and examples for diagnostic checking in linear regression models. Furthermore, some generic tools for inference in parametric models are provided.
r-locfit 1.5-9.1 — Local regression, likelihood and density estimation
This package provides functions used for local regression, likelihood and density estimation.
r-loomr 0.2.0-1.df0144b — R interface for loom files
This package provides an R interface to access, create, and modify loom files. loomR aims to be completely compatible with loompy.
r-lpsolve 5.6.13 — R interface to Lp_solve to solve linear/integer programs
Lp_solve is software for solving linear, integer and mixed integer programs. This implementation supplies a "wrapper" function in C and some R functions that solve general linear/integer problems, assignment problems, and transportation problems.
r-lubridate 1.7.4 — Make dealing with dates a little easier
This package provides functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. The 'lubridate' package has a consistent and memorable syntax that makes working with dates easy and fun.
r-magic 1.5-8 — Create and investigate magic squares
This package provides a collection of efficient, vectorized algorithms for the creation and investigation of magic squares and hypercubes, including a variety of functions for the manipulation and analysis of arbitrarily dimensioned arrays.
r-magrittr 1.5 — A forward-pipe operator for R
Magrittr provides a mechanism for chaining commands with a new forward-pipe operator, %>%. This operator will forward a value, or the result of an expression, into the next function call/expression. There is flexible support for the type of right-hand side expressions. For more information, see package vignette. To quote Rene Magritte, "Ceci n'est pas un pipe."
r-maldiquant 1.18 — Quantitative analysis of mass spectrometry data
This package provides a complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions.
r-manipulatewidget 0.10.0 — Add even more interactivity to interactive charts
This package lets you create in just a few lines of R code a nice user interface to modify the data or the graphical parameters of one or multiple interactive charts. It is useful to quickly explore visually some data or for package developers to generate user interfaces easy to maintain.
r-mapproj 1.2.6 — Map projection in R
This package converts latitude/longitude into projected coordinates.
r-maps 3.3.0 — Draw geographical maps
This package provies an R module for display of maps. Projection code and larger maps are in separate packages ('mapproj' and 'mapdata').
r-maptools 0.9-3 — Tools for reading and handling spatial objects
This package provides a set of tools for manipulating and reading geographic data, in particular ESRI Shapefiles. It includes binary access to GSHHG shoreline files. The package also provides interface wrappers for exchanging spatial objects with other R packages.
r-markdown 0.8 — Markdown rendering for R
This package provides R bindings to the Sundown Markdown rendering library (https://github.com/vmg/sundown). Markdown is a plain-text formatting syntax that can be converted to XHTML or other formats.
r-marray 1.58.0 — Exploratory analysis for two-color spotted microarray data
This package contains class definitions for two-color spotted microarray data. It also includes fuctions for data input, diagnostic plots, normalization and quality checking.
r-mass 7.3-50 — Support functions and datasets for Venables and Ripley's MASS
This package provides functions and datasets for the book "Modern Applied Statistics with S" (4th edition, 2002) by Venables and Ripley.
r-matrix 1.2-14 — Sparse and dense matrix classes and methods
This package provides classes and methods for dense and sparse matrices and operations on them using LAPACK and SuiteSparse.
r-matrixmodels 0.4-1 — Modelling with sparse and dense matrices
This package models with sparse and dense matrix matrices, using modular prediction and response module classes.
r-matrixstats 0.54.0 — Methods applying to vectors and matrix rows and columns
This package provides methods operating on rows and columns of matrices, e.g.
rowSds(). There are also some vector-based methods, e.g.
weightedMedians(). All methods have been optimized for speed and memory usage.
r-mclust 5.4.1 — Gaussian mixture modelling for model-based clustering etc.
This package provides Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.
r-memoise 1.1.0 — Memoise functions for R
This R package allows to cache the results of a function so that when you call it again with the same arguments it returns the pre-computed value.
r-metap 1.0 — Meta-analysis of significance values
The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and a routine for graphical display.
r-methylkit 1.6.1 — DNA methylation analysis from high-throughput bisulfite sequencing results
MethylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from Reduced representation bisulfite sequencing (RRBS) and its variants, but also target-capture methods and whole genome bisulfite sequencing. It also has functions to analyze base-pair resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq.
r-mgcv 1.8-24 — Mixed generalised additive model computation
GAMs, GAMMs and other generalized ridge regression with multiple smoothing parameter estimation by GCV, REML or UBRE/AIC. The library includes a
gam() function, a wide variety of smoothers, JAGS support and distributions beyond the exponential family.
r-mhsmm 0.4.16 — Inference for hidden Markov and semi-Markov models
r-mhsmm package implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some unobserved (or hidden) state. Also, this package is suitable for equidistant time series data, with multivariate and/or missing data. Allows user defined emission distributions.
r-mice 3.3.0 — Multivariate imputation by chained equations
Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in http://doi.org/10.18637/jss.v045.i03. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.
r-microbenchmark 1.4-4 — Accurate timing functions for R
This package provides infrastructure to accurately measure and compare the execution time of R expressions.
r-mime 0.5 — R package to map filenames to MIME types
This package guesses the MIME type from a filename extension using the data derived from /etc/mime.types in UNIX-type systems.
r-minimal 3.5.0 — Environment for statistical computing and graphics
R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.
r-miniui 0.1.1.1 — Shiny UI widgets for small screens
This package provides UI widget and layout functions for writing Shiny apps that work well on small screens.
r-minqa 1.2.4 — Derivative-free optimization algorithms by quadratic approximation
This package provides a derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M. J. D. Powell.
r-mitml 0.3-6 — Tools for multiple imputation in multilevel modeling
This package provides tools for multiple imputation of missing data in multilevel modeling. It includes a user-friendly interface to the packages pan and jomo, and several functions for visualization, data management and the analysis of multiply imputed data sets.
r-mixtools 1.1.0 — Tools for analyzing finite mixture models
This package provides a collection of R functions for analyzing finite mixture models.
r-mnormt 1.5-5 — Multivariate normal and "t" distributions
This package provides functions for computing the density and the distribution function of multivariate normal and "t" random variables, and for generating random vectors sampled from these distributions. Probabilities are computed via non-Monte Carlo methods.
r-modelmetrics 1.2.0 — Rapid calculation of model metrics
Written in C++ using
Rcpp, this package provides a collection of metrics for evaluating models.
r-modelr 0.1.2 — Helper functions for modelling in pipelines
Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.
r-modeltools 0.2-22 — Tools and classes for statistical models
This package provides a collection of tools to deal with statistical models. The functionality is experimental and the user interface is likely to change in the future.
r-moonbook 0.2.3 — Functions and datasets for the book by Keon-Woong Moon
This package provides several analysis-related functions for the book entitled "R statistics and graph for medical articles" (written in Korean), version 1, by Keon-Woong Moon with Korean demographic data with several plot functions.
r-mosaic 1.4.0 — Mathematics, statistics, and computation teaching utilities
This package contain data sets and utilities from Project MOSAIC used to teach mathematics, statistics, computation and modeling. Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.
r-mosaiccore 0.6.0 — Common utilities for mosaic family packages
Common utilities used in other Mosaic family packages are collected here.
r-mosaicdata 0.17.0 — Data sets for project Mosaic
This package provides data sets from project Mosaic http://mosaic-web.org used to teach mathematics, statistics, computation and modeling.
r-motifrg 1.24.0 — Discover motifs in high throughput sequencing data
This package provides tools for discriminative motif discovery in high throughput genetic sequencing data sets using regression methods.
r-msnbase 2.6.3 — Base functions and classes for MS-based proteomics
This package provides basic plotting, data manipulation and processing of mass spectrometry based proteomics data.
r-msnid 1.14.0 — Utilities for LC-MSn proteomics identifications
This package extracts tandem mass spectrometry (MS/MS) ID data from mzIdentML (leveraging the mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximum number of identifications while not exceeding a specified false discovery rate. It also contains a number of utilities to explore the MS/MS results and assess missed and irregular enzymatic cleavages, mass measurement accuracy, etc.
r-multitaper 1.0-14 — Multitaper spectral analysis tools
This package implements multitaper spectral estimation techniques using prolate spheroidal sequences (Slepians) and sine tapers for time series analysis. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates.
r-multtest 2.36.0 — Resampling-based multiple hypothesis testing
This package can do non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of T- and F-statistics (including T-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with T-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted P-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.
r-munsell 0.5.0 — Munsell colour system
The Munsell package contains Functions for exploring and using the Munsell colour system.