This package is a collection of tools to load R packages and automatically generate BibTeX files citing them as well as load and cache plain-text and Excel formatted data stored on GitHub, and from other sources.

This is a package for the analysis of music and speech. Analyze music and speech, extract features like MFCCs, handle wave files and their representation in various ways, read MP3, read MIDI, perform steps of a transcription, ...

Cyclomatic complexity is a software metric, used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code. This package provides tools to compute this metric.

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.

LIGER is a package for integrating and analyzing multiple single-cell datasets, developed and maintained by the Macosko lab. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors.

This package handles very large numbers in R. Real numbers are held using their natural logarithms, plus a logical flag indicating sign. The package includes a vignette that gives a step-by-step introduction to using S4 methods.

This package OrgMassSpecR is an extension of the R statistical computing language. It contains functions to assist with organic or biological mass spectrometry data analysis. Mass spectral libraries are available as companion packages.

This package combines a forecast of a time series, using the function forecast, with the dynamic plots from dygraphs.

This package provides functions to deal with binary classification problems in the presence of imbalanced classes. Synthetic balanced samples are generated according to ROSE (Menardi and Torelli, 2013). Functions that implement more traditional remedies to the class imbalance are also provided, as well as different metrics to evaluate a learner accuracy. These are estimated by holdout, bootstrap or cross-validation methods.

This package provides datasets to accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage.

This package provides a collection of regular expression tools associated with the qdap package that may be useful outside of the context of discourse analysis. Tools include removal/extraction/replacement of abbreviations, dates, dollar amounts, email addresses, hash tags, numbers, percentages, citations, person tags, phone numbers, times, and zip codes.

This package was designed to find an acceptable Python binary that matches version and feature constraints.

This package provides output formats and utilities for authoring books and technical documents with R Markdown.

This package creates scatterpie plots, especially useful for plotting pies on a map.

This package tracks reading and writing within R scripts that are organized into a directed acyclic graph. It contains an interactive Shiny application adaprApp(). It uses Git and file hashes to track version histories of inputs and outputs.

This package provides a consistent, flexible and easy to use tool to parse and convert strings into cases like snake or camel among others.

The clusterCrit package provides an implementation of the following indices: Czekanowski-Dice, Folkes-Mallows, Hubert Γ, Jaccard, McNemar, Kulczynski, Phi, Rand, Rogers-Tanimoto, Russel-Rao or Sokal-Sneath. ClusterCrit defines several functions which compute internal quality indices or external comparison indices. The partitions are specified as an integer vector giving the index of the cluster each observation belongs to.

This package helps you to automate R package and project setup tasks that are otherwise performed manually. This includes setting up unit testing, test coverage, continuous integration, Git, GitHub integration, licenses, Rcpp, RStudio projects, and more.

This package provides a minimal set of predicates and assertions used by the assertive package. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package provides functions and datasets for bootstrapping from the book "Bootstrap Methods and Their Application" by A.C. Davison and D.V. Hinkley (1997, CUP), originally written by Angelo Canty for S.

This package provides UI widget and layout functions for writing Shiny apps that work well on small screens.

This package contains R-functions to perform an fMRI analysis as described in Polzehl and Tabelow (2019) <DOI:10.1007/978-3-030-29184-6>, Tabelow et al. (2006) <DOI:10.1016/j.neuroimage.2006.06.029>, Polzehl et al. (2010) <DOI:10.1016/j.neuroimage.2010.04.241>, Tabelow and Polzehl (2011) <DOI:10.18637/jss.v044.i11>.

This package provides recursive partitioning functions for classification, regression and survival trees.

This package provides a lightweight unit testing framework. Main features:

1. install tests with the package;

2. test results are treated as data that can be stored and manipulated;

3. test files are R scripts interspersed with test commands, that can be programmed over;

4. fully automated build-install-test sequence for packages;

5. skip tests when not run locally (e.g. on CRAN);

6. flexible and configurable output printing;

7. compare computed output with output stored with the package;

8. run tests in parallel;

9. extensible by other packages;

10. report side effects.