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I've been trying out the reversible jump functions in WinBUGS for variable selection and for the most part I was pleasantly surprised at how easy to use the interface is. Thanks Dave Lunn for a great add-on package! I have run into a couple of problems/limitations I'm wondering if anyone knows how to solve/work around. 1) Is there a nice way to leave out the constant (intercept) term? As I understand it, by saying eg. mu[1:Ncases] <- jump.lin.pred(X[1:Ncases,1:Q], k, tau.beta) I automatically include an intercept in all models considered. It this true? Anyway to exclude it? 2) I would like to restrict the beta's (the hidden regression coeffients) to be non-negative. As things stand these beta's get a multinormal prior with mean 0 (correct?). Any suggestions? Thanks! -- Michael O'Dell Phonetics University of Tampere ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list