This package provides tools to find the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library. There is support for approximate as well as exact searches, fixed radius searches and bd as well as kd trees. The distance is computed using the L1 (Manhattan, taxicab) metric.

This package preloads class unions for defining/loading core OOMPA tools. It also includes vectorized operations for row-by-row means, variances, and t-tests. Finally, it provides new colorschemes.

This package provides functions for performing phylogenetic comparative analyses.

ZeroMQ is a well-known library for high-performance asynchronous messaging in scalable, distributed applications. This package provides high level R wrapper functions to easily utilize ZeroMQ. The main focus is on interactive client/server programming frameworks. A few wrapper functions compatible with rzmq are also provided.

Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in ggplot2.

This package provides tools for the analysis of complex survey samples. The provided features include: summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples; variances by Taylor series linearisation or replicate weights; post-stratification, calibration, and raking; two-phase subsampling designs; graphics; PPS sampling without replacement; principal components, and factor analysis.

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

The ade4 package contains data analysis functions to analyze ecological and environmental data in the framework of Euclidean exploratory methods.

This package provides a set of predicates and assertions for checking the properties of numbers. 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 S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.

The Splancs package was written as an enhancement to S-Plus for display and analysis of spatial point pattern data; it has been ported to R and is in "maintenance mode".

This package provides a simple yet powerful logging utility. Based loosely on log4j, futile.logger takes advantage of R idioms to make logging a convenient and easy to use replacement for cat and print statements.

This package provides portable tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes and their children; restart processes. It can read the standard output and error of the processes, using non-blocking connections. processx can poll a process for standard output or error, with a timeout. It can also poll several processes at once.

This package improves the user experience of Shiny apps by helping to provide feedback when required inputs are missing, or input values are not valid.

This package is meant to ease the creation of time-to-event (i.e. survival) endpoint figures. The modular functions create figures ready for publication. Each of the functions that add to or modify the figure are written as proper ggplot2 geoms or stat methods, allowing the functions from this package to be combined with any function or customization from ggplot2 and other ggplot2 extension packages.

The tidy modeling "verse" is a collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.

Building modeling packages is hard. A large amount of effort generally goes into providing an implementation for a new method that is efficient, fast, and correct, but often less emphasis is put on the user interface. A good interface requires specialized knowledge about S3 methods and formulas, which the average package developer might not have. The goal of hardhat is to reduce the burden around building new modeling packages by providing functionality for preprocessing, predicting, and validating input.

Facilitates easy analysis of factorial experiments, including purely within-Ss designs (a.k.a. "repeated measures"), purely between-Ss designs, and mixed within-and-between-Ss designs. The functions in this package aim to provide simple, intuitive and consistent specification of data analysis and visualization. Visualization functions also include design visualization for pre-analysis data auditing, and correlation matrix visualization. Finally, this package includes functions for non-parametric analysis, including permutation tests and bootstrap resampling. The bootstrap function obtains predictions either by cell means or by more advanced/powerful mixed effects models, yielding predictions and confidence intervals that may be easily visualized at any level of the experiment's design.

The glmnet package provides efficient procedures for fitting the entire lasso or elastic-net regularization path for linear and Poisson regression, as well as logistic, multinomial, Cox, multiple-response Gaussian and grouped multinomial models. The algorithm uses cyclical coordinate descent in a path-wise fashion.

This package provides tools for maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting. It extends the lme4 package.

This package provides utilities for dealing with distributions. Functionality includes sample skewness and kurtosis, log-histogram, tail plots, moments by integration, changing the point about which a moment is calculated, functions for testing distributions using inversion tests and the Massart inequality. Also included is an implementation of the incomplete Bessel K function.

This package provides means to run simulations for adaptive seamless designs with and without early outcomes for treatment selection and subpopulation type designs.

This package provides the datasets to support the Fish Stock Assessment (FSA) package.

This package provides a complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions.