Thanks a lot for help in advance. I am switching from matlab to R and I guess I need some time to get rolling. I was wondering why this code : 
 
> fit.0 <- lm( Response ~ 1, data = ds3)
> step(fit.0,scope=list(upper=~.,lower=~1),data=ds3)
Start:  AIC= -32.66 
 Response ~ 1 

Call:
lm(formula = Response ~ 1, data = ds3)
Coefficients:
(Intercept)  
      1.301  
 
 
is not working different from the following:
 
> 
> cnames <- dimnames(ds3)[[2]]
> cnames <- cnames[-444]        # last col is Response
> 
> fmla <- as.formula(paste(" ~ ",paste(cnames,collapse="+")))
> step(fit.0,scope=list(upper=fmla,lower=~1),data=ds3)
Start:  AIC= -32.66 
 Response ~ 1  
> fmla <- as.formula(paste(" ~ ",paste(cnames,collapse="+")))
> fit.s <- step(fit.0,scope=list(upper=fmla,lower=~1),data=ds3)

Step:  AIC= -Inf 
 Response ~ ENTP9324 + CH1W0281 
           Df Sum of Sq     RSS  AIC
<none>                        0 -Inf
- CH1W0281  3   0.00381 0.00381 -115
- ENTP9324  9         1       1  -34

The dataframe ds3 is 17 by 444 and I understand it is not smart thing to run stepwise regression. What I wondered is if I pass the 'upper=~.' , it seems step() thinks the full model is current one. Not adding anymore. If this is the right answer, is there a better way than creating fmla argument in the above?
 
Thanks!
 
-Young.
 

		
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