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r-bma
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Package for Bayesian model averaging and variable selection for linear models, generalized linear models and survival models (cox regression).
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2025-04-22 |
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r-ash
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David Scott's ASH routines ported from S-PLUS to R.
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2025-04-22 |
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django-treebeard
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Efficient tree implementations for Django
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2025-04-22 |
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r-dosnow
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Provides a parallel backend for the %dopar% function using Luke Tierney's snow package.
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2025-04-22 |
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r-prroc
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Computes the areas under the precision-recall (PR) and ROC curve for weighted (e.g., soft-labeled) and unweighted data. In contrast to other implementations, the interpolation between points of the PR curve is done by a non-linear piecewise function. In addition to the areas under the curves, the curves themselves can also be computed and plotted by a specific S3-method. References: Davis and Goadrich (2006) <doi:10.1145/1143844.1143874>; Keilwagen et al. (2014) <doi:10.1371/journal.pone.0092209>; Grau et al. (2015) <doi:10.1093/bioinformatics/btv153>.
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2025-04-22 |
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r-pmcmr
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Note, that the 'PMCMR' package is superseded by the novel 'PMCMRplus' package. The 'PMCMRplus' package contains all functions from 'PMCMR' and many more parametric and non-parametric multiple comparison procedures, one-factorial trend tests, as well as improved method functions, such as print, summary and plot. The 'PMCMR' package is no longer maintained, but kept for compatibility of reverse depending packages for some time.
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2025-04-22 |
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r-penalized
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Fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.
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2025-04-22 |
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r-outliers
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A collection of some tests commonly used for identifying outliers.
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2025-04-22 |
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r-nozzle.r1
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The Nozzle package provides an API to generate HTML reports with dynamic user interface elements based on JavaScript and CSS (Cascading Style Sheets). Nozzle was designed to facilitate summarization and rapid browsing of complex results in data analysis pipelines where multiple analyses are performed frequently on big data sets. The package can be applied to any project where user-friendly reports need to be created.
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2025-04-22 |
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r-nor1mix
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Onedimensional Normal Mixture Models Classes, for, e.g., density estimation or clustering algorithms research and teaching; providing the widely used Marron-Wand densities. Efficient random number generation and graphics; now fitting to data by ML (Maximum Likelihood) or EM estimation.
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2025-04-22 |
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r-nleqslv
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Solve a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.
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2025-04-22 |
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r-multitaper
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Implements multitaper spectral analysis using discrete prolate spheroidal sequences (Slepians) and sine tapers. 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.
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2025-04-22 |
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r-minpack.lm
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The nls.lm function provides an R interface to lmder and lmdif from the MINPACK library, for solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support for lower and upper parameter bounds. The implementation can be used via nls-like calls using the nlsLM function.
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2025-04-22 |
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r-optparse
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A command line parser inspired by Python's 'optparse' library to be used with Rscript to write "#!" shebang scripts that accept short and long flag/options.
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2025-04-22 |
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r-downloader
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Provides a wrapper for the download.file function, making it possible to download files over HTTPS on Windows, Mac OS X, and other Unix-like platforms. The 'RCurl' package provides this functionality (and much more) but can be difficult to install because it must be compiled with external dependencies. This package has no external dependencies, so it is much easier to install.
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2025-04-22 |
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r-dorng
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Provides functions to perform reproducible parallel foreach loops, using independent random streams as generated by L'Ecuyer's combined multiple-recursive generator [L'Ecuyer (1999), <DOI:10.1287/opre.47.1.159>]. It enables to easily convert standard %dopar% loops into fully reproducible loops, independently of the number of workers, the task scheduling strategy, or the chosen parallel environment and associated foreach backend.
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2025-04-22 |
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r-discriminer
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Functions for Discriminant Analysis and Classification purposes covering various methods such as descriptive, geometric, linear, quadratic, PLS, as well as qualitative discriminant analyses
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2025-04-22 |
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r-dbplyr
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A 'dplyr' back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features works with any database that has a 'DBI' back end; more advanced features require 'SQL' translation to be provided by the package author.
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2025-04-22 |
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r-corrplot
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A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
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2025-04-22 |
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r-compute.es
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Several functions are available for calculating the most widely used effect sizes (ES), along with their variances, confidence intervals and p-values. The output includes ES's of d (mean difference), g (unbiased estimate of d), r (correlation coefficient), z' (Fisher's z), and OR (odds ratio and log odds ratio). In addition, NNT (number needed to treat), U3, CLES (Common Language Effect Size) and Cliff's Delta are computed. This package uses recommended formulas as described in The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).
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2025-04-22 |
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r-checkpoint
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The goal of checkpoint is to solve the problem of package reproducibility in R. Specifically, checkpoint allows you to install packages as they existed on CRAN on a specific snapshot date as if you had a CRAN time machine. To achieve reproducibility, the checkpoint() function installs the packages required or called by your project and scripts to a local library exactly as they existed at the specified point in time. Only those packages are available to your project, thereby avoiding any package updates that came later and may have altered your results. In this way, anyone using checkpoint's checkpoint() can ensure the reproducibility of your scripts or projects at any time. To create the snapshot archives, once a day (at midnight UTC) Microsoft refreshes the Austria CRAN mirror on the "Microsoft R Archived Network" server (<https://mran.microsoft.com/>). Immediately after completion of the rsync mirror process, the process takes a snapshot, thus creating the archive. Snapshot archives exist starting from 2014-09-17.
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2025-04-22 |
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django-versatileimagefield
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A drop-in replacement for django ImageField that provides a flexible, intuitive and easily-extensible interface for quickly creating new images from the one assigned to the field.
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2025-04-22 |
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r-venndiagram
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A set of functions to generate high-resolution Venn and Euler plots. Includes handling for several special cases, including two-case scaling, and extensive customization of plot shape and structure.
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2025-04-22 |
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r-r.rsp
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The RSP markup language makes any text-based document come alive. RSP provides a powerful markup for controlling the content and output of LaTeX, HTML, Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. 'Today's date is <%=Sys.Date()%>'. Contrary to many other literate programming languages, with RSP it is straightforward to loop over mixtures of code and text sections, e.g. in month-by-month summaries. RSP has also several preprocessing directives for incorporating static and dynamic contents of external files (local or online) among other things. Functions rstring() and rcat() make it easy to process RSP strings, rsource() sources an RSP file as it was an R script, while rfile() compiles it (even online) into its final output format, e.g. rfile('report.tex.rsp') generates 'report.pdf' and rfile('report.md.rsp') generates 'report.html'. RSP is ideal for self-contained scientific reports and R package vignettes. It's easy to use - if you know how to write an R script, you'll be up and running within minutes.
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2025-04-22 |
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r-ptw
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Parametric Time Warping aligns patterns, i.e. it aims to put corresponding features at the same locations. The algorithm searches for an optimal polynomial describing the warping. It is possible to align one sample to a reference, several samples to the same reference, or several samples to several references. One can choose between calculating individual warpings, or one global warping for a set of samples and one reference. Two optimization criteria are implemented: RMS (Root Mean Square error) and WCC (Weighted Cross Correlation). Both warping of peak profiles and of peak lists are supported.
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2025-04-22 |
