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This package provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.
This package provides an R interface to the C libstemmer library that implements Porter's word stemming algorithm for collapsing words to a common root to aid comparison of vocabulary. Currently supported languages are Danish, Dutch, English, Finnish, French, German, Hungarian, Italian, Norwegian, Portuguese, Romanian, Russian, Spanish, Swedish and Turkish.
Call job::job(<code here>) to run R code as an RStudio job and keep your console free in the meantime. This allows for a productive workflow while testing (multiple) long-running chunks of code. It can also be used to organize results using the RStudio Jobs GUI or to test code in a clean environment. Two RStudio Addins can be used to run selected code as a job.
This package computes model II simple linear regression using ordinary least squares (OLS), major axis (MA), standard major axis (SMA), and ranged major axis (RMA).
Annoy is a small C++ library for Approximate Nearest Neighbors written for efficient memory usage as well an ability to load from and save to disk. This package provides an R interface.
This package provides classes and methods to locate, setup, subset, navigate and iterate file sets, i.e. sets of files located in one or more directories on the file system. The API is designed such that these classes can be extended via inheritance to provide a richer API for special file formats. Moreover, a specific name format is defined such that filenames and directories can be considered to have full names which consists of a name followed by comma-separated tags. This adds additional flexibility to identify file sets and individual files.
This package provides data sets used for demonstrating or testing model-related packages.
This is a package for binomial and Poisson regression for clustered data, fixed and random effects with bootstrapping.
This package provides an all relevant feature selection wrapper algorithm. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).
This package provides an infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). It also provides C implementations of the association mining algorithms Apriori and Eclat.
This package provides font files that can be used by the showtext package.
This package provides the full texts for Jane Austen's six completed novels, ready for text analysis. These novels are "Sense and Sensibility", "Pride and Prejudice", "Mansfield Park", "Emma", "Northanger Abbey", and "Persuasion".
Uniform manifold approximation and projection is a technique for dimension reduction. This package provides an interface to the UMAP algorithm in R, including a translation of the original algorithm into R.
This package provides a cross-platform Perl-based R function to create Excel 2003 (XLS) and Excel 2007 (XLSX) files from one or more data frames. Each data frame will be written to a separate named worksheet in the Excel spreadsheet. The worksheet name will be the name of the data frame it contains or can be specified by the user.
This package provides estimators for multinomial logit models in their conditional logit and baseline logit variants, with or without random effects, with or without overdispersion. Random effects models are estimated using the PQL technique (based on a Laplace approximation) or the MQL technique (based on a Solomon-Cox approximation). Estimates should be treated with caution if the group sizes are small.
This package parses a fitted R model object, and returns a formula in Tidy Eval code that calculates the predictions. It works with several database backends because it leverages dplyr and dbplyr for the final SQL translation of the algorithm. It currently supports lm(), glm(), randomForest(), ranger(), earth(), xgb.Booster.complete(), cubist(), and ctree() models.
This is a package for the analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported.
This package provides the cumulative distribution function (CDF), quantile, and statistical power calculator for a collection of thresholding Fisher's p-value combination methods, including Fisher's p-value combination method, truncated product method and, in particular, soft-thresholding Fisher's p-value combination method which is proven to be optimal in some context of signal detection. The p-value calculator for the omnibus version of these tests are also included.
This package provides a mutation analysis tool that discovers cancer driver genes with frequent mutations in protein signalling sites such as post-translational modifications (phosphorylation, ubiquitination, etc). The Poisson generalized linear regression model identifies genes where cancer mutations in signalling sites are more frequent than expected from the sequence of the entire gene. Integration of mutations with signalling information helps find new driver genes and propose candidate mechanisms to known drivers.
This package provides classes and methods for dense and sparse matrices and operations on them using LAPACK and SuiteSparse.
This package performs the Baumgartner-Weiss-Schindler two-sample test of equal probability distributions (doi:10.2307/2533862). It also performs similar rank-based tests for equal probability distributions due to Neuhauser (doi:10.1080/10485250108832874) and Murakami (doi:10.1080/00949655.2010.551516).
This package provides new statistics, new geometries and new positions for ggplot2 and a suite of functions to facilitate the creation of statistical plots.
This package implements various estimators of entropy, such as the shrinkage estimator by Hausser and Strimmer, the maximum likelihood and the Millow-Madow estimator, various Bayesian estimators, and the Chao-Shen estimator. It also offers an R interface to the NSB estimator. Furthermore, it provides functions for estimating Kullback-Leibler divergence, chi-squared, mutual information, and chi-squared statistic of independence. In addition there are functions for discretizing continuous random variables.
This is a package for the estimation, validation and prediction of kriging models.