Includes a collection of shiny applications to demonstrate or to explore fundamental item response theory (IRT) concepts such as estimation, scoring, and multidimensional IRT models.

Shared parameter models for the joint modeling of longitudinal and time-to-event data using MCMC; Dimitris Rizopoulos (2016) <doi:10.18637/jss.v072.i07>.

Evaluate specific panels in different aspects: i) Simulation tools related to pedigree researches; ii) calculation for systemic effectiveness indicators, such as probability of exclusion (PE).

This package provides a simple progress bar showing estimated remaining time. Multiple forecast methods and user defined forecast method for the remaining time are supported.

Conducts and simulates the MABOUST design, including making interim decisions to stop a treatment for inferiority or stop the trial early for superiority or equivalency.

Implementation of parametric and semiparametric mixture cure models based on existing R packages. See details of the models in Peng and Yu (2020) <ISBN: 9780367145576>.

Statistical entropy analysis of network data as introduced by Frank and Shafie (2016) <doi:10.1177/0759106315615511>, and a in textbook which is in progress.

Facilitates the gathering of biodiversity occurrence data from disparate sources. Metadata is managed throughout the process to facilitate reporting and enhanced ability to repeat analyses.

This package provides a database management tool built as a shiny application. Connect to various databases to send queries, upload files, preview tables, and more.

This package provides a simple interface in the form of R6 classes for executing tasks in parallel, tracking their progress, and displaying accurate progress bars.

Data sets from Ramsey, F.L. and Schafer, D.W. (2013), "The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed)", Cengage Learning.

This package provides a variety of functions to estimate time-dependent true/false positive rates and AUC curves from a set of censored survival data.

Test your data! An extension of the testthat unit testing framework with a family of functions and reporting tools for checking and validating data frames.

Pure R implementation of Apache Thrift. This library doesn't require any code generation. To learn more about Thrift go to <https://thrift.apache.org>.

Converting structured data from tables into XML format using predefined templates ensures consistency and flexibility, making it ideal for data exchange, reporting, and automated workflows.

Data frame class for storing collective movement data (e.g. fish schools, ungulate herds, baboon troops) collected from GPS trackers or computer vision tracking software.

This package provides a crawler for programmatically navigating THREDDS Data Server (<https://www.unidata.ucar.edu/software/tds/>) catalogs, and access dataset metadata and resources.

Conduct unit root tests based on EViews (<https://eviews.com>) routines and report them in tables. EViews (Econometric Views) is a commercial software for econometrics.

The LabKey client library for R makes it easy for R users to load live data from a LabKey Server, <https://www.labkey.com/>, into the R environment for analysis, provided users have permissions to read the data. It also enables R users to insert, update, and delete records stored on a LabKey Server, provided they have appropriate permissions to do so.

An R and Repast integration tool for running individual-based (IbM) simulation models developed using Repast Simphony Agent-Based framework directly from R code supporting multicore execution. This package integrates Repast Simphony models within R environment, making easier the tasks of running and analyzing model output data for automated parameter calibration and for carrying out uncertainty and sensitivity analysis using the power of R environment.

This package provides a client library for making requests from Ruby. It uses a simple method chaining system for building requests, similar to Python's Requests.

EBNF is a Ruby parser for W3C EBNF and a parser generator for PEG and LL(1). Also includes parsing modes for ISO EBNF and ABNF.

hdWGCNA is an R package for performing weighted gene co-expression network analysis in high dimensional -omics such as single-cell RNA-seq or spatial transcriptomics.

NbClust provides 30 indexes for determining the optimal number of clusters in a data set and offers the best clustering scheme from different results to the user.