Recent content by sarikan

Hi frbl, Thanks a lot for taking the time to respond to this. It is never too late for useful responses :)

Ok, I have to confess that I've been bitten by my lack of proper understanding of the word intractable. My native language is not English, and I've taken intractable as impossible to calculate, which was wrong. I would still appreciate your input though, is not this term a bit subjective?

Greetings, I've been using Bayesian methods and especially Gibbs sampling to work on models of various complexity, and I've always accepted the pretty much standard textbook explanation as a sensible justification for using sampling methods: sometimes the posterior distributions of Bayesian...

Thanks. A good overall paper it appears. I'll read it in detail. Conjugacy is useful, though I approach it with some hesitation, since my work may end up with arbitrary distributions, where conjugacy may not be possible. I think I've found the right term for what I'm looking for by the way...

Greetings, Maybe I'm getting a little bit confused, but I'm looking for resources which explain how to update parameters of a Bayesian network as a result of observations. There are various inference methods, but unless I'm missing something here, these methods produce a posterior...

Indeed. Especially in a Bayesian text. Thanks for the response. Kind regards

Hi, I'm trying to follow a text about Bayesian statistics, and the author is using the following notation to describe a random variable which has normal distribution: p(x | µ, σ2) = (Gaussian density function here) In a Bayesian text, this notation is confusing, since it makes me think...