Overlay a grid on a 2D distribution of random variables Z(x,y) and assign all such variables to the nearest grid node. Then consider the distribution of F(i,j) = (ZMAX-ZMIN)(i,j) for any grid node with nearby data. For simplicity, assume that the original random variables are (locally) normally distributed and that all collected at any node have the same mean and standard deviation. What is the distribution of F?
My reason for asking is that I am trying to automatically select a grid row and column spacing to use in grid-based surface modeling and one intuitive criteria is to get a "dense enough" grid that the largest ZMAX-ZMIN for any single grid node is small relative to the range of Z values in the input data set. (Well, intuitive to me.) Then I started wondering what I might conclude if the sampled mean plus a couple of standard deviations for the population of such node variables was small. And then I got confused. I am guessing that the distribution of F is standard problem in statistics when the data are normal: Given M samples from N(0,1), what is the distribution of Zmax-Zmin? But I don't have the right "standard" statistics book. Hmmm. Maybe I am gathering information about the nugget for a data set? Thanks, Steven Zoraster -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
