Hello Jim, Please reply to the list - you'll have a much better chance of getting useful suggestions.
> OK so some addition info. I know each of the X2 is in (0,1). Is there any > method available? I don't think that's sufficient to estimate b, at least not in my experience of fitting Bayesian models with MCMC. To get any sort of precise posterior for b I think you would need to know that, for instance, X2 is correlated with X1 in some way, or that it can be described by a particular Beta distribution etc. I'd be happy to be corrected by others here who know much more than I do but if the best prior you can come up with for X2 is uniform in (0,1) I think you have insufficient information to proceed. Michael On 24 October 2010 09:28, Jim Silverton <jim.silver...@gmail.com> wrote: > I am trying to estimate the parameter b. > I have Y and X1 which I know and they are both random. However, I also have > X2 which I don't know and is also random. I want to estimat b from the > model: > > Y = b*X1 + ( 1 - b ) * X2 > > so my constraints areCan anyone offer some suggestions. The values of Y and > X1 are both pvalues > so they are constrained in (0,1). > > OK so some addition info. I know each of the X2 is in (0,1). Is there any > method available? > Jim > > On Sat, Oct 23, 2010 at 8:31 AM, Michael Bedward <michael.bedw...@gmail.com> > wrote: >> >> Hi Jim, >> >> You don't mention whether you have any prior information regarding X2 >> that can be used to constrain values imputed for it. I think you will >> need some because without it values sampled for b and X2 respectively >> will just "see-saw" against each other. >> >> Michael >> >> >> On 22 October 2010 18:37, Jim Silverton <jim.silver...@gmail.com> wrote: >> > Hello everyone, >> > I am trying to estimate the parameter b. >> > I have Y and X1 which I know and they are both random. However, I also >> > have >> > X2 which I don't know and is also random. I want to estimat b from the >> > model: >> > >> > Y = b*X1 + ( 1 - b ) * X2 >> > >> > Can anyone offer some suggestions. The values of Y and X1 are both >> > pvalues >> > so they are constrained in (0,1). >> > >> > -- >> > Thanks, >> > Jim. >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> > > > > > -- > Thanks, > Jim. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
