In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Multivariate meta-regression models are commonly used in settings where the response variable is naturally multidimensional. Such settings are common in cardiovascular and diabetes studies where the ...

This is a preview. Log in through your library . Abstract Inference is considered for a location parameter given a random sample. Outliers are not explicitly modelled, but rejection of extreme ...

Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...

Background Bayesian networks (BN) are directed acyclic graphs derived from empirical data that describe the dependency and probability structure. It may facilitate understanding of complex ...