Download data and metadata from the 'Bundesbank SDMX Web
    Service API' found at
    <https://www.bundesbank.de/en/statistics/time-series-databases/help-for-sdmx-web-service/web-service-interface-data>.

A fast and intuitive batch effect removal tool for single-cell data. BBKNN is originally used in the 'scanpy' python package, and now can be used with 'Seurat' seamlessly.

Supervised learning using Boltzmann Bayes model inference, 
    which extends naive Bayes model to include interactions. Enables 
    classification of data into multiple response groups based on a large 
    number of discrete predictors that can take factor values of 
    heterogeneous levels. Either pseudo-likelihood or mean field 
    inference can be used with L2 regularization, cross-validation, and 
    prediction on new data. 
    <doi:10.18637/jss.v101.i05>.

Miscellaneous helper functions for and from B. Bischl and
    some other guys, mainly for package development.

The method models RNA-seq reads using a mixture of 3 beta-binomial distributions to generate posterior probabilities for genotyping bi-allelic single nucleotide polymorphisms. Elena Vigorito, Anne Barton, Costantino Pitzalis, Myles J. Lewis and Chris Wallace (2023) <doi:10.1093/bioinformatics/btad393> "BBmix: a Bayesian beta-binomial mixture model for accurate genotyping from RNA-sequencing."

Methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.

A system to build, visualise and evaluate Bayesian belief networks. The methods are described in Stafford et al. (2015) <doi:10.12688/f1000research.5981.1>.

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'.