In article <[EMAIL PROTECTED]>, David Heiser <[EMAIL PROTECTED]> wrote:
>"Safa Gurcan" <[EMAIL PROTECTED]> wrote in message >news:[EMAIL PROTECTED] >> Dear Folks, >> In multiple regression analysis; model summary (R2, adjusted R2) and ANOVA >> results display in the output screen. I used ridge regression analysis to >> my data in SYSTAT but, didn't see any of the results above except >> standardized and unstandardized coefficient and lamda . Does Ridge >> regression have R2 and SEM ? How de we understand that the unstandardized >> regression coefficients explained the variation of dependent variable? >> thanks for advice. >> Safa Gurcan >------------------------------------- >One of the problems with ridge analysis is that there is no defined stopping >point. Ridge analysis is good when one wants to make "good" predictions of >Y values where the X values are near to and exceed the limits of the sample >space. In many cases involving physical (chemical) data, the predictions >exceed physical constraints, and by using ridge analysis, one "relaxes" the >fit to where the predictions are withing "reality". Standard fit measures >are not much help here to establish a "stopping point". My paper in _Bayesian Statistics 3_ gives an explicit formula for the loss in using a "wrong" ridge prior. I suggest the Bayesian approach be used rather than "classical" procedures which are ad hoc with no real basis. -- 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/ . =================================================================
