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I'm sorry, but I'm lost, are we talking about this likelihood function? I'm guessing no, since that's an object defined in a statistical space, not in a probabi

• lalaithion 6y ago
  Oftentimes, a “likelihood function” is generalized from that definition to refer to any non-normalized function which is still treated like a probability distribution. Any function with a finite integral over the real line can be turned into a probability distribution easily, and there are other functions that can be used in places where you would normally use a probability function, even when they don’t integrate to a finite value over the real line. (For example, improper priors in Bayesian analysis.) “Function that can in some contexts be treated like a probability distribution” is just too long.
• moultano 6y ago
  Yes, that's the right likelihood function. To get probabilities distributions out of the products in the post, all you have to do is normalize them. That would be equivalent to applying bayes rule and combining independent evidence about a parameter with an uninformative prior. Normalizing doesn't change the shapes, so I left out the details.