This package provides a genetic algorithm plus derivative optimizer.

This package provides utilities to understand and describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion such as Highest Density Interval (HDI), and indices used for null-hypothesis testing (such as ROPE percentage and pd).

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions.

This package provides unified plotting tools for statistics commonly used, such as GLM, time series, PCA families, clustering and survival analysis. The package offers a single plotting interface for these analysis results and plots in a unified style using the ggplot2 package.

This package provides tools to create dynamic, submission-ready manuscripts, which conform to American Psychological Association manuscript guidelines. It provides R Markdown document formats for manuscripts (PDF and Word) and revision letters (PDF). Helper functions facilitate reporting statistical analyses or create publication-ready tables and plots.

This package provides tools for pretty, human readable formatting of quantities.

In order to smoothly animate the transformation of polygons and paths, many aspects needs to be taken into account, such as differing number of control points, changing center of rotation, etc. The transformr package provides an extensive framework for manipulating the shapes of polygons and paths and can be seen as the spatial brother to the tweenr package.

This package provides common functionality for the dynverse packages. dynverse is created to support the development, execution, and benchmarking of trajectory inference methods.

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

The aim of the ggplot2 package is to aid in visual data investigations. This focus has led to a lack of facilities for composing specialized plots. This package aims to be a collection of mainly new statistics and geometries that fills this gap.

Aster models (Geyer, Wagenius, and Shaw, 2007, <doi:10.1093/biomet/asm030>; Shaw, Geyer, Wagenius, Hangelbroek, and Etterson, 2008, <doi:10.1086/588063>; Geyer, Ridley, Latta, Etterson, and Shaw, 2013, <doi:10.1214/13-AOAS653>) are exponential family regression models for life history analysis. They are like generalized linear models except that elements of the response vector can have different families (e.2g., some Bernoulli, some Poisson, some zero-truncated Poisson, some normal) and can be dependent, the dependence indicated by a graphical structure. Discrete time survival analysis, life table analysis, zero-inflated Poisson regression, and generalized linear models that are exponential family (e.g., logistic regression and Poisson regression with log link) are special cases. Main use is for data in which there is survival over discrete time periods and there is additional data about what happens conditional on survival (e.g., number of offspring). Uses the exponential family canonical parameterization (aster transform of usual parameterization). There are also random effects versions of these models.

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

This is a collection of econometric functions for performance and risk analysis. This package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.

This package provides utility functions for easy parallelism in R. This includes some reexports from other packages, utility functions for splitting and parallelizing over blocks, and choosing and setting the number of cores used.

This package provides probability mass, distribution, quantile, random-variate generation, and method-of-moments parameter-estimation functions for the Delaporte distribution with parameterization based on Vose (2008). The Delaporte is a discrete probability distribution which can be considered the convolution of a negative binomial distribution with a Poisson distribution. Alternatively, it can be considered a counting distribution with both Poisson and negative binomial components. It has been studied in actuarial science as a frequency distribution which has more variability than the Poisson, but less than the negative binomial.

This R package provides access to the code and data sets published by the statistics blog FiveThirtyEight.

Multivariate data sets often differ in several factors or derived statistical parameters, which have to be selected for a valid interpretation. Basing this selection on traditional statistical limits leads occasionally to the perception of losing information from a data set. This package provides tools to calculate these limits on the basis of the mathematical properties of the distribution of the analyzed items.

r-kmer is an R package for rapidly computing distance matrices and clustering large sequence datasets using fast alignment-free k-mer counting and recursive k-means partitioning.

This package provides primitives for visualizing distributions using ggplot2 that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized.

Hnswlib is a C++ library for approximate nearest neighbors. This package provides a minimal R interface by relying on the Rcpp package.

This package provides functions to perform k-prototypes partitioning clustering for mixed variable-type data according to Z.Huang (1998): Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Variables, Data Mining and Knowledge Discovery 2, 283-304.

This package provides helpers for reordering factor levels (including moving specified levels to front, ordering by first appearance, reversing, and randomly shuffling), and tools for modifying factor levels (including collapsing rare levels into other, "anonymizing", and manually "recoding").

This package provides a range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.

This package provides color palettes that have been generated mostly from Wes Anderson movies.