nicolexz wrote: > I need to sample a random variable from truncated distribution > everytime in MCMC. Suppose, the upper (a) and lower (b) bounds are > far from the location parameter (c) and the scale parameter is > relatively small, i.e,. b<=a<=c, and c is far greater than a and b. > The chance to sample using slice sampling is trivival. It's almost > impossible to sample it from such a truncated distribution. However, > the problem is quite often in some cases. What should I do in dealing > with this scenario? > > Many thanks, > Nicole
Take a look at Robert's accept-reject algorithm in Robert, C. P. (1995). Simulation of truncated normal variables. Statistics and Computing, 5, 121-125. -- Timothy R. Johnson, Department of Statistics, University of Idaho [EMAIL PROTECTED] . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
