The A() function calculates the A statistic, a nonparametric measure of effect size for two independent groups thatâ s also known as the probability of superiority (Ruscio, 2008), along with its standard error and a confidence interval constructed using bootstrap methods (Ruscio & Mullen, 2012). Optional arguments can be specified to calculate variants of the A statistic developed for other research designs (e.g., related samples, more than two independent groups or related samples; Ruscio & Gera, 2013). <DOI: 10.1037/1082-989X.13.1.19>. <DOI: 10.1080/00273171.2012.658329>. <DOI: 10.1080/00273171.2012.738184>.

Rho is used to test the generalization of inter rater reliability (IRR) statistics. Calculating rho starts by generating a large number of simulated, fully-coded data sets: a sizable collection of hypothetical populations, all of which have a kappa value below a given threshold -- which indicates unacceptable agreement. Then kappa is calculated on a sample from each of those sets in the collection to see if it is equal to or higher than the kappa in then real sample. If less than five percent of the distribution of samples from the simulated data sets is greater than actual observed kappa, the null hypothesis is rejected and one can conclude that if the two raters had coded the rest of the data, we would have acceptable agreement (kappa above the threshold).

This package implements the Zig-Zag algorithm (Bierkens, Fearnhead, Roberts, 2016) <arXiv:1607.03188> applied and Bouncy Particle Sampler <arXiv:1510.02451> for a Gaussian target and Student distribution.

Estimates the rearranged dependence measure ('RDM') of two continuous random variables for different underlying measures. Furthermore, it provides a method to estimate the (SI)-rearrangement copula using empirical checkerboard copulas. It is based on the theoretical results presented in Strothmann et al. (2022) <arXiv:2201.03329> and Strothmann (2021) <doi:10.17877/DE290R-22733>.

This package provides the Jester Dataset for package recommenderlab.

Stan implementation of the Theory of Visual Attention (TVA; Bundesen, 1990; <doi:10.1037/0033-295X.97.4.523>) and numerous convenience functions for generating, compiling, fitting, and analyzing TVA models.

Easily Download Analysis-Ready Crash Data from the U.S. National Highway Traffic Safety Administration.

Allows one to use Osmium Tool (<https://osmcode.org/osmium-tool/>) from R. Osmium is a multipurpose command line tool that enables one to manipulate and analyze OpenStreetMap files through several different commands. Currently, this package does not aim to offer functions that cover the entire Osmium API, instead making available functions that wrap only a very limited set of its features.

Parse scientific names using gnparser (<https://github.com/gnames/gnparser>), written in Go. gnparser parses scientific names into their component parts; it utilizes a Parsing Expression Grammar specifically for scientific names.

Climacell is a weather platform that provides hyper-local forecasts and weather data. This package enables the user to query the core layers of the time line interface of the Climacell v4 API <https://www.climacell.co/weather-api/>. This package requires a valid API key. See vignettes for instructions on use.

This package provides a series of functions to call AD Model Builder (i.e., compile and run models) from within R, read the results back into R as admb objects, and provide standard accessors (i.e. coef(), vcov(), etc.).

Exploration of pharmacometrics data involves both general tools (transformation and plotting) and specific techniques (non-compartmental analysis). This kind of exploration is generally accomplished by utilizing different packages. The purpose of ruminate is to create a shiny interface to make these tools more broadly available while creating reproducible results.

Automated test assembly of linear and adaptive tests using the mixed-integer programming. The full documentation and tutorials are at <https://github.com/xluo11/Rata>.

An implementation of robust boosting algorithms for regression in R. This includes the RRBoost method proposed in the paper "Robust Boosting for Regression Problems" (Ju X and Salibian-Barrera M. 2020) <doi:10.1016/j.csda.2020.107065>. It also implements previously proposed boosting algorithms in the simulation section of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) <doi:10.1214/aos/1013203451>) and Robloss (Lutz et al. (2008) <doi:10.1016/j.csda.2007.11.006>).

Create an R Journal Rmarkdown template article, that will generate html and pdf versions of your paper. Check that the paper folder has all the required components needed for submission. Examples of R Journal publications can be found at <https://journal.r-project.org>.

This package provides functions for conducting robust variance estimation (RVE) meta-regression using both large and small sample RVE estimators under various weighting schemes. These methods are distribution free and provide valid point estimates, standard errors and hypothesis tests even when the degree and structure of dependence between effect sizes is unknown. Also included are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.

This package provides methods and tools for implementing functional singular spectrum analysis and related techniques.

R interface to DSDP semidefinite programming library. The DSDP software is a free open source implementation of an interior-point method for semidefinite programming. It provides primal and dual solutions, exploits low-rank structure and sparsity in the data, and has relatively low memory requirements for an interior-point method.

EZR (Easy R) adds a variety of statistical functions, including survival analyses, ROC analyses, metaanalyses, sample size calculation, and so on, to the R commander. EZR enables point-and-click easy access to statistical functions, especially for medical statistics. EZR is platform-independent and runs on Windows, Mac OS X, and UNIX. Its complete manual is available only in Japanese (Chugai Igakusha, ISBN: 978-4-498-10918-6, Nankodo, ISBN: 978-4-524-21861-5, Ohmsha, ISBN: 978-4-274-22632-8), but an report that introduced the investigation of EZR was published in Bone Marrow Transplantation (Nature Publishing Group) as an Open article. This report can be used as a simple manual. It can be freely downloaded from the journal website as shown below. This report has been cited in more than 14,000 scientific articles.

The getconf command-line tool provided by libc allows querying of a large number of system variables. This package provides similar functionality.

This package provides wrappers around base::grep() where the first argument is standardized to take the data object. This makes it less of a pain to use regular expressions with magrittr or other pipe operators.

Uses a combination of raytracing and multiple hill shading methods to produce 2D and 3D data visualizations and maps. Includes water detection and layering functions, programmable color palette generation, several built-in textures for hill shading, 2D and 3D plotting options, a built-in path tracer, Wavefront OBJ file export, and the ability to save 3D visualizations to a 3D printable format.

Streamlines the creation of reproducible analytical pipelines using default.nix expressions generated via the rix package for reproducibility. Define derivations in R', Python or Julia', chain them into a composition of pure functions and build the resulting pipeline using Nix as the underlying end-to-end build tool. Functions to plot the pipeline as a directed acyclic graph are included, as well as functions to load and inspect intermediary results for interactive analysis. User experience heavily inspired by the targets package.

This package produces population distribution of disease risk and statistical risk categories, and predicts risks for individuals with genotype information.