This is a package for estimation of a sparse inverse covariance matrix using a lasso (L1) penalty. Facilities are provided for estimates along a path of values for the regularization parameter.

This package performs estimation of physical activity and sedentary behavior variables from activPAL events files.

This package extends the fitdistr function of the MASS package with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left-censored, right-censored and interval-censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME) and maximum goodness-of-fit estimation (MGE) methods (available only for non-censored data). Weighted versions of MLE, MME and QME are available.

Analyze count time series with excess zeros. Two types of statistical models are supported: Markov regression and state-space models. They are also known as observation-driven and parameter-driven models respectively in the time series literature. The functions used for Markov regression or observation-driven models can also be used to fit ordinary regression models with independent data under the zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB) assumption. The package also contains miscellaneous functions to compute density, distribution, quantile, and generate random numbers from ZIP and ZINB distributions.

This package provides tools to identify global ("unknown" or "free") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal. The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.

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 functions for testing affine hypotheses on the regression coefficient vector in regression models with autocorrelated errors.

This package can be used to conduct post hoc analyses of resampling results generated by models. For example, if two models are evaluated with the root mean squared error (RMSE) using 10-fold cross-validation, there are 10 paired statistics. These can be used to make comparisons between models without involving a test set.

This package converts back and forth between two representations of a convex polytope: as solution of a set of linear equalities and inequalities and as convex hull of set of points and rays. Also does linear programming and redundant generator elimination. All functions can use exact infinite-precision rational arithmetic.

This package provides functions for reading and writing data stored by some versions of Epi Info, Minitab, S, SAS, SPSS, Stata, Systat and Weka and for reading and writing some dBase files.

This package serves two purposes:

1. Provide a comfortable R interface to query the Google server for static maps, and

2. Use the map as a background image to overlay plots within R. This requires proper coordinate scaling.

This package allows for data objects in R to be rendered as HTML tables using the JavaScript library DataTables (typically via R Markdown or Shiny). The DataTables library has been included in this R package.

This package provides an implementation of the ACME estimator, described in Wolpert (2015), ACME: A Partially Periodic Estimator of Avian & Chiropteran Mortality at Wind Turbines. Unlike most other models, this estimator supports decreasing-hazard Weibull model for persistence; decreasing search proficiency as carcasses age; variable bleed-through at successive searches; and interval mortality estimates. The package provides, based on search data, functions for estimating the mortality inflation factor in Frequentist and Bayesian settings.

This package provides an R library to generate Sankey network graphs in R and Shiny via the D3 visualization library.

This package provides functions for fitting and working with generalized additive models, as described in chapter 7 of "Statistical Models in S" (Chambers and Hastie (eds), 1991), and "Generalized Additive Models" (Hastie and Tibshirani, 1990).

This package provides an interface to Amazon Web Services application integration services, including Simple Queue Service (SQS) message queue, Simple Notification Service (SNS) publish/subscribe messaging, and more.

This package provides functions for plotting graphical shapes such as ellipses, circles, cylinders, arrows, ...

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.

This package provides a wrapper for the Intro.js library. This package makes it easy to include step-by-step introductions, and clickable hints in a Shiny application. It supports both static introductions in the UI, and programmatic introductions from the server-side.

The r-abd package contains data sets and sample code for the Analysis of biological data by Michael Whitlock and Dolph Schluter.

This package provides airline on-time data for all flights departing NYC in 2013. It also includes useful metadata on airlines, airports, weather, and planes.

This package implements an efficient O(n) algorithm based on bucket-sorting for fast computation of standard clustering comparison measures. Available measures include adjusted Rand index (ARI), normalized information distance (NID), normalized mutual information (NMI), adjusted mutual information (AMI), normalized variation information (NVI) and entropy.

This package provides an R interface to the C libstemmer library that implements Porter's word stemming algorithm for collapsing words to a common root to aid comparison of vocabulary. Currently supported languages are Danish, Dutch, English, Finnish, French, German, Hungarian, Italian, Norwegian, Portuguese, Romanian, Russian, Spanish, Swedish and Turkish.

It contains functions that solve least squares linear regression problems under linear equality/inequality constraints. Functions for solving quadratic programming problems are also available, which transform such problems into least squares ones first.