Calculate and optimize dynamic performance ratings of association football 
  teams competing in matches, in accordance with the method used in 
  the research paper "Determining the level of ability of football teams by 
  dynamic ratings based on the relative discrepancies in scores between adversaries", 
  by Constantinou and Fenton (2013) 
  <doi:10.1515/jqas-2012-0036>    
  This dynamic rating system has proven to provide superior 
  results for predicting association football outcomes.

Scored responses and responses times from the Canadian subsample of the PISA 2018 assessment, accessible as the "Cognitive items total time/visits data file" by OECD (2020) <https://www.oecd.org/pisa/data/2018database/>.

A wrapper around the 'Parsing Expression Grammar Template Library', a C++11 library for generating
    Parsing Expression Grammars, that makes it accessible within Rcpp. With this, developers can implement
    their own grammars and easily expose them in R packages.

Provides tools for estimating the statistical power of Interrupted
    Time Series (ITS) designs, with a focus on healthcare applications. The
    package supports prospective power calculations before a study begins, and
    retrospective assessments of whether a completed study was adequately powered.
    It includes functions to estimate nuisance parameters (baseline, residual
    standard deviation, autocorrelation) from data observed before the
    intervention, and to
    estimate power via Monte Carlo simulation for single-site and multi-site
    designs. Utility functions for design optimisation sweeps and publication-
    ready plots are also provided.

Collection of pivotal algorithms 
             for: relabelling the MCMC chains in order to undo the label 
             switching problem in Bayesian mixture models;
             fitting sparse finite mixtures;
             initializing the centers of the classical k-means algorithm 
             in order to obtain a better clustering solution. 
             For further details see
             Egidi, Pappadà, Pauli and Torelli (2018b)<ISBN:9788891910233>.