On 09 Feb 2014, at 10:56 , Paul Parsons <pparsons...@gmail.com> wrote:
> > Many thanks, Peter. Creating a wrapper function for integrand using > Vectorize, and then integrating the wrapper, does indeed solve the problem. I > tried your final suggestion, but the variable x still gets passed into > pmvnorm inside the new mean and variance matrix, leading to the same problem > when the integrate function vectorizes x. You missed the point: There's nothing to integrate if you do it that way. All you need is the marginal distribution of the differences. -pd > All the best > Paul > > On 8 Feb 2014, at 18:04, peter dalgaard wrote: > >> ou almost said it yourself: Your integrand doesn't vectorize. The direct >> culprit is the following: >> >> If x is a vector, what is lower=c(x,x,x,x)? A vector of length 4*length(x). >> And pmvnorm doesn't vectorize so it wouldn't help to have lower= as a matrix >> (e.g., cbind(x,x,x,x)) instead. >> >> A straightforward workaround is to Vectorize() your function. Possibly more >> efficient to put an mapply() of sorts around the pmvnorm call. >> >> However, wouldn't it be more obvious to work out the mean and variance >> matrix of (x1-x5, x2-x5, x3-x5, x4-x5) and then just pmvnorm(... >> lower=c(0,0,0,0), upper=c(Inf, Inf, Inf, Inf))?? > -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ 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.
