Inspired by the the futile.logger R package and logging Python module, this utility provides a flexible and extensible way of formatting and delivering log messages with low overhead.

This package contains the datasets and a few functions for use with the practicals outlined in Appendix A of the book Statistical Models (Davison, 2003, Cambridge University Press). The practicals themselves can be found at http://statwww.epfl.ch/davison/SM/.

This package creates lots of colorful plots in a multitude of variations. Try a demo of the LSD by running demotour().

This package provides functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.

This package fits multivariate generalized linear mixed models and related models. This is done using Markov chain Monte Carlo techniques.

This package provides an R wrapper for libnabo, an exact or approximate k nearest neighbour library which is optimised for low dimensional spaces (e.g. 3D). nabor includes a knn function that is designed as a drop-in replacement for the RANN function nn2. In addition, objects which include the k-d tree search structure can be returned to speed up repeated queries of the same set of target points.

This package provides a unified pipeline to clean, prepare, plot, and run basic analyses on pupillometry experiments.

The base functions for set operations in R can be used for only two sets. This package RVenn provides functions for dealing with multiple sets. It uses purr to find the union, intersection and difference of three or more sets. This package also provides functions for pairwise set operations among several sets. Further, based on ggplot2 and ggforce, a Venn diagram can be drawn for two or three sets. For bigger data sets, a clustered heatmap showing the presence or absence of the elements of the sets can be drawn based on the pheatmap package. Finally, enrichment test can be applied to two sets whether an overlap is statistically significant or not.

This package provides tools to parse simple .ini configuration files to an structured list. Users can manipulate this resulting list with lapply() functions. This same structured list can be used to write back to file after modifications.

This package provides tools to create some specific Space-Filling Design (SFD) and to test their quality.

Circular layout is an efficient way to visualise huge amounts of information. This package provides an implementation of circular layout generation in R as well as an enhancement of available software. Its flexibility is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, it gives users more convenience and freedom to design figures for better understanding complex patterns behind multi-dimensional data.

This package provides different high-level graphics functions for displaying large datasets, displaying circular data in a very flexible way, finding local maxima, brewing color ramps, drawing nice arrows, zooming 2D-plots, creating figures with differently colored margin and plot region. In addition, the package contains auxiliary functions for data manipulation like omitting observations with irregular values or selecting data by logical vectors, which include NAs. Other functions are especially useful in spectroscopy and analyses of environmental data: robust baseline fitting, finding peaks in spectra, converting humidity measures.

This package provides functions for reading and writing data stored by some versions of Epi Info, Minitab, S, SAS, SPSS, Stata, Systat and Weka and for reading and writing some dBase files.

This package provides a command line parser to be used with Rscript to write shebang scripts that gracefully accept positional and optional arguments and automatically generate usage notices.

This is a package for the computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate, and multimodal regression.

This package provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.

This package provides a solver for generalized estimation equations.

The tictoc package provides the timing functions tic and toc that can be nested. It provides an alternative to system.time() with a different syntax similar to that in another well-known software package. tic and toc are easy to use, and are especially useful when timing several sections in more than a few lines of code.

This package contains an S3 class with methods for totally ordered indexed observations. It is particularly aimed at irregular time series of numeric vectors/matrices and factors.

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.

This package provides an iteration of the DEoptim function. It performs global optimization by differential evolution.

This package provides tools for functional enrichment analysis, gene identifier conversion and mapping homologous genes across related organisms via the g:Profiler toolkit.

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.

This package provides a C++ header library for using the libsoda-cxx library with R. The C++ header reimplements the lsoda function from the ODEPACK library for solving initial value problems for first order ordinary differential equations. The C++ header can be used by other R packages by linking against this package. The C++ functions can be called inline using Rcpp. Finally, the package provides an ode function to call from R.