This package provides a collection of miscellaneous 3d plots, including isosurfaces.

Similarly to the FNN package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. The implementation is based on cover trees introduced by Alina Beygelzimer, Sham Kakade, and John Langford (2006) doi:10.1145/1143844.1143857.

This package provides a collection of tools for building RAxML supermatrix using PHYLIP or aligned FASTA files. These functions will be useful for building large phylogenies using multiple markers.

This package provides tools for reading .xls and .sbj files which are written by the proprietary program z-Tree for developing and carrying out economic experiments.

This package allows for testing of non-nested models. It includes tests of model distinguishability and of model fit that can be applied to both nested and non-nested models. The package also includes functionality to obtain confidence intervals associated with AIC and BIC.

This package provides users not only with a function to readily calculate the higher-order partial and semi-partial correlations but also with statistics and p-values of the correlation coefficients.

This package provides functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, and more.

This package provides support for measurement units in R vectors, matrices and arrays: automatic propagation, conversion, derivation and simplification of units; raising errors in case of unit incompatibility. It is compatible with the POSIXct, Date and difftime classes.

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 implements heuristics for the quadratic assignment problem (QAP). Currently only a simulated annealing heuristic is available.

This package provides a set of tools to facilitate package development and make R a more user-friendly place. It is intended mostly for developers (or anyone who writes/shares functions). It provides a simple, powerful and flexible way to check the arguments passed to functions. The developer can easily describe the type of argument needed. If the user provides a wrong argument, then an informative error message is prompted with the requested type and the problem clearly stated--saving the user a lot of time in debugging.

This package provides functions for Constraint Based Simulation using Flux Balance Analysis and informative analysis of the data generated during simulation.

This package extends the fitdistr function of the MASS package with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left-censored, right-censored and interval-censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME) and maximum goodness-of-fit estimation (MGE) methods (available only for non-censored data). Weighted versions of MLE, MME and QME are available.

This is a package for exploratory graphical analysis of multivariate data, specifically gene expression data with different projection methods: principal component analysis, correspondence analysis, spectral map analysis.

Users may want to align plots with associated information that requires axes to be exactly matched in subplots, e.g. hierarchical clustering with a heatmap. This package provides utilities to align associated subplots to a main plot at different sides (left, right, top and bottom) with axes exactly matched.

automap performs an automatic interpolation by automatically estimating the variogram and then calling gstat.

This is a package for ratios of count data such as obtained from RNA-seq are modelled using Bayesian statistics to derive posteriors for effects sizes. This approach is described in Erhard & Zimmer (2015) <doi:10.1093/nar/gkv696> and Erhard (2018) <doi:10.1093/bioinformatics/bty471>.

Tools for integrating spatially-misaligned GIS datasets. Part of the Sub-National Geospatial Data Archive System.

This package provides an easy and simple way to read, write and display bitmap images stored in the PNG format. It can read and write both files and in-memory raw vectors.

This package provides tools for the analysis and visualization of bilateral asymmetry in parasitic infections.

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 provides a system for embedded scientific computing and reproducible research with R. The OpenCPU server exposes a simple but powerful HTTP API for RPC and data interchange with R. This provides a reliable and scalable foundation for statistical services or building R web applications. The OpenCPU server runs either as a single-user development server within the interactive R session, or as a multi-user stack based on Apache2.

This package contains R functions and datasets detailed in the book "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan.

Lambert W x F distributions are a generalized framework to analyze skewed, heavy-tailed data. It is based on an input/output system, where the output random variable (RV) Y is a non-linearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). The transformed RV Y has a Lambert W x F distribution. This package contains functions to model and analyze skewed, heavy-tailed data the Lambert Way: simulate random samples, estimate parameters, compute quantiles, and plot/ print results nicely. The most useful function is Gaussianize, which works similarly to scale, but actually makes the data Gaussian. A do-it-yourself toolkit allows users to define their own Lambert W x MyFavoriteDistribution and use it in their analysis right away.