This package provides a set of psychometric tools for cognitive diagnosis modeling based on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) doi:10.1007/s11336-011-9207-7 and its extensions, including the sequential G-DINA model by Ma and de la Torre (2016) doi:10.1111/bmsp.12070 for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre doi:10.1177/0146621613479818 for polytomous attributes. Joint attribute distribution can be independent, saturated, higher-order, loglinear smoothed or structured. Q-matrix validation, item and model fit statistics, model comparison at test and item level and differential item functioning can also be conducted. A graphical user interface is also provided.

This package provides routines for Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear Models.

This package provides a set of simple functions that transforms longitudinal data to estimate the cosinor linear model as described in Tong (1976). Methods are given to summarize the mean, amplitude and acrophase, to predict the mean annual outcome value, and to test the coefficients.

This package provides a genetic algorithm plus derivative optimizer.

This package provides a collection of ggplot2 color palettes inspired by plots in scientific journals, data visualization libraries, science fiction movies, and TV shows.

Ggfittext is a ggplot2 extension for fitting text into boxes.

This package provides functions that:

1. find the minimum/maximum of a linear or quadratic function,

2. sample an underdetermined or overdetermined system,

3. solve a linear system Ax=B for the unknown x.

It includes banded and tridiagonal linear systems. The package calls Fortran functions from LINPACK.

This package provides an easy way to fill an environment with active bindings that call a C++ function.

This package provides functions for animations in statistics, covering topics in probability theory, mathematical statistics, multivariate statistics, non-parametric statistics, sampling survey, linear models, time series, computational statistics, data mining and machine learning. These functions may be helpful in teaching statistics and data analysis. Also provided in this package are a series of functions to save animations to various formats, e.g. GIF, HTML pages, PDF, and videos. PDF animations can be inserted into Sweave / knitr easily.

This package implements a parametric bootstrap test and a Kenward Roger modification of F-tests for linear mixed effects models and a parametric bootstrap test for generalized linear mixed models.

This package provides common base and stats methods for rle objects, aiming to make it possible to treat them transparently as vectors.

This package provides an implementation of heatmaps that offers more control over dimensions and appearance.

This package provides a URL-safe base64 encoder and decoder. In contrast to RFC3548, the 62nd character (+) is replaced with -, the 63rd character (/) is replaced with _. Furthermore, the encoder does not fill the string with trailing =. The resulting encoded strings comply to the regular expression pattern [A-Za-z0-9_-] and thus are safe to use in URLs or for file names. The package also comes with a simple base32 encoder/decoder suited for case insensitive file systems.

This package provides a derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M. J. D. Powell.

This package provides ACE and AVAS methods for choosing regression transformations.

This package provides an R wrapper for the special functions and quasi random number generators of the GNU Scientific Library.

Some basic features of MUMPS are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: PORD, METIS, SCOTCH.

This package provides an interface to Amazon Web Services cost management services, including cost and usage reports, budgets, pricing, and more.

This package implements a data structure similar to hashes in Perl and dictionaries in Python but with a purposefully R flavor. For objects of appreciable size, access using hashes outperforms native named lists and vectors.

This package provides iterative methods for matrix completion that use nuclear-norm regularization. The package includes procedures for centering and scaling rows, columns or both, and for computing low-rank single value decompositions (SVDs) on large sparse centered matrices (i.e. principal components).

This package provides easy-to-use and versatile functions to output R objects in HTML format.

This package provides a collection of lexical hash tables, dictionaries, and word lists.

The R kernel for the Jupyter environment executes R code which the front-end (Jupyter Notebook or other front-ends) submits to the kernel via the network.

This package implements shadowtextGrob() for grid and geom_shadowtext() layer for ggplot2. These functions draw text grob with background shadow.