Functionality for performing a principled reference analysis in the Bayesian normal-normal hierarchical model used for Bayesian meta-analysis, as described in Ott, Plummer and Roos (2021) <doi:10.1002/sim.9076>. Computes a reference posterior, induced by a minimally informative improper reference prior for the between-study (heterogeneity) standard deviation. Determines additional proper anti-conservative (and conservative) prior benchmarks. Includes functions for reference analyses at both the posterior and the prior level, which, given the data, quantify the informativeness of a heterogeneity prior of interest relative to the minimally informative reference prior and the proper prior benchmarks. The functions operate on data sets which are compatible with the 'bayesmeta' package.

Infers V-D-J (Variable-Diversity-Joining) haplotypes and gene
    deletions from AIRR-seq (Adaptive Immune Receptor Repertoire sequencing)
    data for Ig (Immunoglobulin) and TR (T cell Receptor) chains, based on J
    (Joining), D (Diversity), or V (Variable) genes as anchor, by adapting a
    Bayesian framework.
    It also calculates a Bayes factor, a number that indicates the certainty level of the inference, for each haplotyped gene.
    Citation:
    Gidoni, et al (2019) <doi:10.1038/s41467-019-08489-3>.
    Peres and Gidoni, et al (2019) <doi:10.1093/bioinformatics/btz481>.

Conduct simulations of the Response Adaptive Block Randomization (RABR) design to evaluate its type I error rate, power and operating characteristics for binary and continuous endpoints. For more details of the proposed method, please refer to Zhan et al. (2021) <doi:10.1002/sim.9104>.

Solves the individual bioenergetic balance for different aquaculture sea fish (Sea Bream and Sea Bass; Brigolin et al., 2014 <doi:10.3354/aei00093>) and shellfish (Mussel and Clam; Brigolin et al., 2009 <doi:10.1016/j.ecss.2009.01.029>; Solidoro et al., 2000 <doi:10.3354/meps199137>). Allows for spatialized model runs and population simulations.