In article <[EMAIL PROTECTED]>, Xinmiao <[EMAIL PROTECTED]> wrote: >Hi,
>I have the following question: suppose one is limited by the total >number of data points (# sampling points * # replicates), in order to >get better curve fitting, which way is more preferable: to have fewer >sampling points and more replicates at each point, or to have more >sampling points and fewer replicates? I suspect that it is the latter, >but I don't know any statistical reference or background for that. Can >someone please kindly help me out here? If one knows the form of the curve, then it is known that for a given number of data points available in a compact set, there is an optimal design which uses few points. For example, if one is interested in the slope of a linear regression on one independent variable, it is known that putting all of the points at the ends is optimal. The optimal design generally leaves no opportunity to test the assumptions, but for example for polynomials of moderately high degree, it is FAR more efficient. There is a large literature on this; I am by no means an expert. -- This address is for information only. I do not claim that these views are those of the Statistics Department or of Purdue University. Herman Rubin, Department of Statistics, Purdue University [EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558 . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
