I need to simulate from a random process and am not sure how to go about it. The process is the probability of an event occuring between a pair of points on a line. (This probability is between 0 and 0.5).
I have estimates of these probabilities for a series of points, their standard errors and the correlation matrix (which is AR(1)). Eg (for 4 points) estimated prob (q): 0.1163 0.1280 0.0698 standard error: 0.0320 0.0288 0.0259 asymptotic correlation matrix: 1.0000 -0.0880 1.0000 0.0000 -0.0739 1.0000 The vector q is used in a further analysis, treated as known. I would like to simulate alternative vectors q, which could be used in the further analysis in order to generate some empirical confidence interval. But I don't know where to start with such simulation. (In practice, q has about 50 elements). Although I know how to use cholesky decomposition to simulate dependent variables from a MVN distribution, I am stuck on two counts here: - the distribution for q - how to incorporate the dependence into the simulation. I would appreciate any suggestions. Chris. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html