Defines operating characteristics of Bayesian Adaptive Trials considering a generalised linear model response via Monte Carlo simulations of Bayesian GLM fitted via integrated Laplace approximations (INLA).

Battery reduction is a method used in data reduction. It uses Gram-Schmidt orthogonal rotations to find out a subset of variables best representing the original set of variables.

Collection of tools to work with European basketball data. Functions available are related to friendly 
	web scraping, data management and visualization. Data were obtained from <https://www.euroleaguebasketball.net/euroleague/>, 
	<https://www.euroleaguebasketball.net/eurocup/> and <https://www.acb.com/>, following the instructions 
        of their respectives robots.txt files, when available. Box score data are available for the three leagues. 
	Play-by-play data are also available for the Spanish league. Methods for analysis include a population pyramid, 
	2D plots, circular plots of players' percentiles, plots of players' monthly/yearly stats, team heatmaps, 
	team shooting plots, team four factors plots, cross-tables with the results of regular season games,
	maps of nationalities, combinations of lineups, possessions-related variables, timeouts,
	performance by periods, personal fouls and offensive rebounds. 
	Please see Vinue (2020) <doi:10.1089/big.2018.0124> and Vinue (2024) <doi:10.1089/big.2023.0177>.

Simulating synthetic clumped isotope dataset, fitting
    linear regression models under Bayesian and non-Bayesian frameworks,
    and generating temperature reconstructions for the same two approaches.
    Please note that models implemented in this package are described
    in Roman-Palacios et al. (2021) <doi:10.1002/essoar.10507995.1>.

A Bayesian hybrid approach for inferring Directed Acyclic Graphs
    (DAGs) for continuous, discrete, and mixed data. The algorithm can use the 
    graph inferred by another more efficient graph inference method as input;
    the input graph may contain false edges or undirected edges but can help
    reduce the search space to a more manageable size. A Bayesian Markov chain
    Monte Carlo algorithm is then used to infer the probability of direction and
    absence for the edges in the network.
    References:
    Martin and Fu (2019) <arXiv:1909.10678>.