New to Bayesian Stats

[Archie]

Hello! I'm fairly new to Bayesian stats and will be using WinBugs to analyze spatial data of West Nile virus. I have a lot to learn and was hoping this forum could answer some of my questions. Thanks all!

Josiah

[Dason]

Hi!



The question you asked was interesting - I hope you know you're in for some pretty complex stuff if you want to do your analysis right! Bayesian statistics is pretty awesome though.

[ledzep]

Hope we'll get chance to learn more about White Nile virus in the due course. Watch out for your hyper-parameters though! Sometimes uninformative priors for you hyper parameters in fact turns out to be informative!!! Welcome to the club.

[Dason]

Sometimes uninformative priors for you hyper parameters in fact turns out to be informative!!! Welcome to the club.

Uninformative priors are pretty much always informative in one way or another.

[ledzep]

Uninformative priors are pretty much always informative in one way or another.

May be they should be called something like "informative uninformative priors".

[Dason]

I kind of like the term 'reference' priors.

[noetsi]

Uninformative priors are pretty much always informative in one way or another.

Isn't that an oxymoron....

It reminds me of John Fox's advice that outliers are nearly always useful, because they clue you into to problems in your theory or misspecified model you really need to know.

[Dason]

We call some priors uninformative because they don't influence the posterior distribution much or they don't give us much information about the parameter of interest beforehand. But it's pretty much impossible to eliminate all information - something that is "uniformative" about a parameter in one sense of the word might not be uninformative about a transformation of that parameter. I'm not a huge fan of the 'uninformative' prior terminology but it does at least get across sort of what one is trying to do with that prior - not provide much information about the parameter before hand.