Re: Bayes factor blues

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Re: Bayes factor blues

michael corning
I guess my first set of questions wasn't clear enough. let me try again, only this time i'll ask them separately.

do we calculate the bayes factor by using the probability of winning *for the winning team?*

this would explain why we use nine instances of .9 (for the nine Reds wins) and one instance of .1 (for the time Blues win) for M1 and .99 and .01 for M2.

if i'm back on track I wonder what I missed in the prose on pages 316-318?

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Re: Bayes factor blues

norman@eecs.qmul.ac.uk
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>do we calculate the bayes factor by using the probability of winning *for the winning team?*

in a sense yet. We have to compute the probability of seeing the observed result (e.g. a win for reds if that is the result) given the model is 'correct'. That is what is meant by P(D | M) where D is the observed result and M is the model M is correct.
So if the model M says there is a 0.9 chance of reds winning this particular match and we observe that reds do actually win that match then P(D | M) = 0.9.

But you have made a mistake when you say:

> and .99 and .01 for M2

The .01 should be .91 because for match 5 model M2 says there is a 0.91 probability that blues win and the result is a blued win.

Norman