Integrates the Groovy scripting language with the R Project for Statistical Computing.

Functions to calculate Sample Number and Average Sample Number for Repetitive Group Sampling Plan Based on Cpk as given in Aslam et al. (2013) (<DOI:10.1080/00949655.2012.663374>).

Useful tools for determining whether two samples are from the same distribution. Utilizes a robust method to address the problematic structure of the similarity graph constructed from high-dimensional data. The method is provided in Yichuan Bai and Lynna Chu (2023) <arXiv:2307.12325>.

This is a library to access the current API of the web speed test service 'GTmetrix'.
    It provides a convenient wrapper to start tests, get reports, and access all kinds of meta data. 
    For more information about using the API please visit <https://gtmetrix.com/api/docs/2.0/>.

Automatic open data acquisition from resources of Polish Head Office
    of Geodesy and Cartography ('Główny Urząd Geodezji i Kartografii')
    (<https://www.gov.pl/web/gugik>).
    Available datasets include various types of numeric, raster and vector data,
    such as orthophotomaps, digital elevation models (digital terrain models,
    digital surface model, point clouds), state register of borders, spatial
    databases, geometries of cadastral parcels, 3D models of buildings, and more.
    It is also possible to geocode addresses or objects using the geocodePL_get()
    function.

Reads in continuous glucose monitor data of many different formats, calculates a host of glycemic variability metrics, and plots glucose over time.

Implementation of the affine-invariant method of Goodman & Weare (2010) <DOI:10.2140/camcos.2010.5.65>, a method of producing Monte-Carlo samples from a target distribution.

DBI/RJDBC interface to h2 database. h2 version 2.3.232 is included.

An R interface to the 'Handsontable' JavaScript library, which is a
    minimalist Excel-like data grid editor.  See <https://handsontable.com/> for details.

The renewal Hawkes (RHawkes) process (Wheatley,
    Filimonov, and Sornette, 2016 <doi:10.1016/j.csda.2015.08.007>) is
    an extension to the classical Hawkes self-exciting point process
    widely used in the modelling of clustered event sequence data.
    This package provides functions to simulate the RHawkes process
    with a given immigrant hazard rate function and offspring birth
    time density function, to compute the exact likelihood of a
    RHawkes process using the recursive algorithm proposed by Chen and
    Stindl (2018) <doi:10.1080/10618600.2017.1341324>, to compute the
    Rosenblatt residuals for goodness-of-fit assessment, and to
    predict future event times based on observed event times up to a
    given time. A function implementing the linear time RHawkes
    process likelihood approximation algorithm proposed in Stindl and
    Chen (2021) <doi:10.1007/s11222-021-10002-0> is also included.