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Luke_A_Somers comments on Where did mathematics begin to disagree between frequentist and Bayesian statistics, and why? - Less Wrong Discussion
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Comments (20)
Your ability to distinguish them that way means that there was a large likelihood ratio from the evidence.
A large likelihood ratio? I have two likelihood functions -- at what values of the parameter arguments should I evaluate them when forming the ratio? Given that one of the versions is nested in the other at the boundary of the parameter space (Gaussian errors versus Student-t errors with degrees of freedom fit to the data), what counts as a large enough likelihood ratio to prefer the more general version of the model?