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I appreciate the theoretical aspects of it as well -- however, I could never get over the notion that bayesians need to use frequentist statistics to judge whether the chain has sufficiently converged... isn't that defeating the entire point?

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Interesting point, but I think the academic culture has taken a pragmatic shift: there aren't many 'pure' bayesians or frequentists left anymore, and the boundary between the two viewpoints has softened. Stats has more of a 'shut up and calculate' mentality about it these days.

>Stats has more of a 'shut up and calculate' mentality about it these days.

I'm happy that the "pure this pure that" fundamentalism has faded into retirement... but shut up and calculate has problems - especially around causality. The "blessings of multiple causes" paper for example.

Then why bother pretending to calculate a posterior distribution when you can do a MLE estimator with regularization or something?

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