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Explain why Bayesian model selection tends to prefer simpler models over complex ones, and state a...

Explain why Bayesian model selection tends to prefer simpler models over complex ones, and state a situation when a more complex model would be preferred.

Math   Statistics-And-Probability   
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Answer #1

The Bayesian approach tends to favor simpler, more parsimonious, models than the Complex one because more the parameters the more the complexity. This can lead to further simplification by allowing the removal of variables that now appear irrelevant to the research hypothesis, yielding less cluttered graphs and making interpretation easier.

When we are working with multivariate data and are dealing with many parameters and there is no way of reducing the number of parameters then we have to prefer the Complex model.

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