Bayesian inference for model selection centres on comparing competing hypotheses by evaluating how well each model explains observed data, accounting for prior beliefs about parameters. The ...
Approximate Bayesian computation (ABC) constitutes a family of likelihood-free methods that have emerged as a cornerstone in statistical inference for complex models where evaluation of the likelihood ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results