This package provides an implementation of a data cube extracted out of dplyr for backward compatibility.

Provide nonparametric methods for mean regression model, modal regression and conditional density estimation in the presence/absence of measurement error. Bandwidth selection is also provided for each method.

This package provides functions to convert a page of plots drawn with the graphics package into identical output drawn with the grid package. The result looks like the original graphics-based plot, but consists of grid grobs and viewports that can then be manipulated with grid functions (e.g., edit grobs and revisit viewports).

This package aims to provide easy-to-use, efficient, flexible and scalable statistical tools. It provides and uses file-backed big matrices via memory-mapping. It provides for instance matrix operations, Principal Component Analysis, sparse linear supervised models, utility functions and more.

This package provides a port of the web-based software DAGitty for analyzing structural causal models (also known as directed acyclic graphs or DAGs). This package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications (d-separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation.

This package provides an implementation of interpreted string literals, inspired by Python's Literal String Interpolation (PEP-0498) and Docstrings (PEP-0257) and Julia's Triple-Quoted String Literals.

This package provides functions to access Twitter's filter, sample, and user streams, and to parse the output into data frames.

This package provides functions, documentation and example data to help divide geographic space into discrete polygons (zones). The functions are motivated by research into the merits of different zoning systems. A flexible ClockBoard zoning system is provided, which breaks-up space by concentric rings and radial lines emanating from a central point.

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.

This package provides tools for the visualization of missing and/or imputed values are introduced, which can be used for exploring the data and the structure of the missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods may help to identify the mechanism generating the missing values and explore the data including missing values. In addition, the quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot methods.

Changepoint implements various mainstream and specialised changepoint methods. These methods are suitable for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included as well.

This package lets you fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.

This is a package for mixture and flexible discriminant analysis, multivariate adaptive regression splines (MARS), BRUTO, and so on.

This package provides functions for obtaining the density, random variates and maximum likelihood estimates of the Zero-truncated Poisson lognormal distribution and their mixture distribution.

This package provides an htmlwidgets interface to billboard.js, a re-usable easy interface JavaScript chart library, based on D3 v4+. Chart types include line charts, scatterplots, bar/lollipop charts, histogram/density plots, pie/donut charts and gauge charts. All charts are interactive, and a proxy method is implemented to smoothly update a chart without rendering it again in shiny apps.

The futile.options subsystem provides an easy user-defined options management system that is properly scoped. This means that options created via futile.options are fully self-contained and will not collide with options defined in other packages.

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

This package provides an R implementation of the Octave package signal, containing a variety of signal processing tools, such as signal generation and measurement, correlation and convolution, filtering, filter design, filter analysis and conversion, power spectrum analysis, system identification, decimation and sample rate change, and windowing.

This package provides a variety of simple fish stock assessment methods.

This package generates well-known integer sequences. The gmp package is adopted for computing with arbitrarily large numbers. Every function has a hyperlink to its corresponding item in the On-Line Encyclopedia of Integer Sequences (OEIS) in the function help page.

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 implements easy-to-use functions to generate 2-7 sets Venn plot in publication quality. ggVennDiagram plot Venn using well-defined geometry dataset and ggplot2. The shapes of 2-4 sets Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which are developed and imported from another package venn. We provide internal functions to integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections of them, then separately plot Venn in three components: set edges, set labels, and regions. From version 1.0, it is possible to customize these components as you demand in ordinary ggplot2 grammar.

This package provides utility functions that enhance the parallel package and support the built-in parallel backends of the future package. For example, availableCores gives the number of CPU cores available to your R process as given by R options and environment variables, including those set by job schedulers on high-performance compute clusters. If none is set, it will fall back to parallel::detectCores. Another example is makeClusterPSOCK, which is backward compatible with parallel::makePSOCKcluster while doing a better job in setting up remote cluster workers without the need for configuring the firewall to do port-forwarding to your local computer.

This package includes tools for marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported.