[R] Stepwise regression and PLS

[=?gb2312?q?Jinsong=20Zhao?=]

Dear all,

I am a newcomer to R. I intend to using R to do stepwise regression and
PLS with a data set (a 55x20 matrix, with one dependent and 19
independent variable). Based on the same data set, I have done the same
work using SPSS and SAS. However, there is much difference between the
results obtained by R and SPSS or SAS.

In the case of stepwise, SPSS gave out a model with 4 independent
variable, but with step(), R gave out a model with 10 and much higher
R2. Furthermore, regsubsets() also indicate the 10 variable is one of
the best regression subset. How to explain this difference? And in the
case of my data set, how many variables that enter the model would be
reasonable?

In the case of PLS, the results of mvr function of pls.pcr package is
also different with that of SAS. Although the number of optimum latent
variables is same, the difference between R2 is much large. Why?

Any comment and suggestion is very appreciated. Thanks in advance!

Best wishes,

Jinsong Zhao

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(Mr.) Jinsong Zhao
Ph.D. Candidate
School of the Environment
Nanjing University
No.22 Hankou Road, Najing 210093
P.R. China
E-mail: zh_jinsong at yahoo.com.cn

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