I have a physically-based model which turns some data into esimates of of a set of parameters, together with their non-diagonal covariance matrix. I now want to test whether these parameters are different from say zero. By analogy with linear regression, where I can test whether the slope or intercept are different from zero using the t-test, I have looked for a multi-variate t-test, and come across the Hotelling T^2 test.
Q. Am I right to think that the Hotelling Test is a fairly general recipe for my problem, given that I have a non-diagonal covariance matrix? Q. Presumably there is more devil in the detail regarding the precise formulation of the hypothesis; for example, if I have three parameters, do I have to formulate a hypothesis for all three e.g. they are all different from zero, or can I do it for just one? Q. Is there a decent reference to describe the above? Mathematical is fine. Q. Are there any alternatives to the Hotelling procedure? Thanks Richard Hindmarsh . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
