Implements a fully Bayesian Markov chain Monte Carlo (MCMC) approach for inferring the topology and Boolean logic transition functions of gene regulatory networks from noisy, binary time-series expression data. Network structure and Boolean rules are sampled jointly from their posterior distribution, providing principled uncertainty quantification rather than a single point estimate. Method described in Han et al. (2014) <doi:10.1371/journal.pone.0115806>.

Features highly configurable search spaces via the 'paradox'
    package and optimizes every user-defined objective function. The
    package includes several optimization algorithms e.g. Random Search,
    Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband
    (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning',
    'mlr3fselect' and 'miesmuschel'.

Functions to fit, via Expectation-Maximization (EM) algorithm, the Bessel and Beta regressions to a data set with a bounded continuous response variable. The Bessel regression is a new and robust approach proposed in the literature. The EM version for the well known Beta regression is another major contribution of this package. See details in the references Barreto-Souza, Mayrink and Simas (2022) <doi:10.1111/anzs.12354> and Barreto-Souza, Mayrink and Simas (2020) <arXiv:2003.05157>.

Provides comprehensive tools for blinded sample size re-estimation (BSSR) 
    in two-arm clinical trials with binary endpoints. Unlike traditional fixed-sample 
    designs, BSSR allows adaptive sample size adjustments during trials while 
    maintaining statistical integrity and study blinding. Implements five exact 
    statistical tests: Pearson chi-squared, Fisher exact, Fisher mid-p, Z-pooled 
    exact unconditional, and Boschloo exact unconditional tests. Supports restricted, 
    unrestricted, and weighted BSSR approaches with exact Type I error control.
    Statistical methods based on Mehrotra et al. (2003) <doi:10.1111/1541-0420.00051> 
    and Kieser (2020) <doi:10.1007/978-3-030-49528-2_21>.