This is a package supporting the analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.

This package provides improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.

This package is an R wrapper around the cubature C library for adaptive multivariate integration over hypercubes. This version provides both hcubature and pcubature routines in addition to a vector interface.

This package provides routines for the analysis of indirectly measured haplotypes. The statistical methods assume that all subjects are unrelated and that haplotypes are ambiguous (due to unknown linkage phase of the genetic markers). The main functions are: haplo.em(), haplo.glm(), haplo.score(), and haplo.power(); all of which have detailed examples in the vignette.

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.

The bit64 package provides serializable S3 atomic 64 bit (signed) integers that can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, characters and factors as well as many elementwise and summary functions. Many fast algorithmic operations such as match and order support interactive data exploration and manipulation and optionally leverage caching.

This package provides a collection of efficient, vectorized algorithms for the creation and investigation of magic squares and hypercubes, including a variety of functions for the manipulation and analysis of arbitrarily dimensioned arrays.

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

This package implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.

The R package ggplot2 is a plotting system based on the grammar of graphics. GGally extends ggplot2 by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.

Zoltar is a website that provides a repository of model forecast results in a standardized format and a central location. It supports storing, retrieving, comparing, and analyzing time series forecasts for prediction challenges of interest to the modeling community. This package provides functions for working with the Zoltar API, including connecting and authenticating, getting information about projects, models, and forecasts, deleting and uploading forecast data, and downloading scores.

svglite is a graphics device that produces clean SVG (Scalable Vector Graphics) output, suitable for use on the web, or hand editing. Compared to the built-in svg(), svglite is considerably faster, produces smaller files, and leaves text as is.

This package estimates optimal cutpoints for binary classification metrics. It also validates performance using bootstrapping. Some methods for more robust cutpoint estimation are supported, e.g. a parametric method assuming normal distributions, bootstrapped cutpoints, and smoothing of the metric values per cutpoint using Generalized Additive Models. Various plotting functions are included.

This package provides a quantitative financial modelling framework to allow users to specify, build, trade, and analyse quantitative financial trading strategies.

Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via the Template Model Builder. Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.

This package provides new statistics, new geometries and new positions for ggplot2 and a suite of functions to facilitate the creation of statistical plots.

This package provides the full texts for Jane Austen's six completed novels, ready for text analysis. These novels are "Sense and Sensibility", "Pride and Prejudice", "Mansfield Park", "Emma", "Northanger Abbey", and "Persuasion".

Tools for working with and comparing sets of points and intervals.

This package is a usability wrapper around snow for easier development of parallel R programs. This package offers e.g. extended error checks, and additional functions. All functions work in sequential mode, too, if no cluster is present or wished. The package is also designed as connector to the cluster management tool sfCluster, but can also used without it.

This package provides an implementation of the Anderson-Darling GoF test with p-value calculation based on Marsaglia's 2004 paper "Evaluating the Anderson-Darling Distribution".

This package can automatically extract statistical null-hypothesis significant testing (NHST) results from articles and recompute the p-values based on the reported test statistic and degrees of freedom to detect possible inconsistencies.

This package provides a collection of tools to evaluate probability density functions, cumulative distribution functions, quantile functions and random numbers for truncated random variables. These functions are provided to also compute the expected value and variance. Q-Q plots can be produced. All the probability functions in the stats, stats4 and evd packages are automatically available for truncation.

This package provides a comprehensive library for date-time manipulations using a new family of orthogonal date-time classes (durations, time points, zoned-times, and calendars) that partition responsibilities so that the complexities of time zones are only considered when they are really needed. Capabilities include: date-time parsing, formatting, arithmetic, extraction and updating of components, and rounding.

This package provides miscellaneous helper functions for the development of R packages.