R help - Nov 2002 - Scaling part of a data frame

I have a 30 x 27 data frame, which I'm trying to scale and transform.
Only I want to scale certain all variables except one (the dependent,
which I want to log+1 transform). I can use split() and then scale() and
log1p(), but I'm wondering if I can do this in one call.

I tried apply(), but I could only get the whole data frame, not a part
of it:
> test <- apply(chin.sub, 2, log1p)    is fine, but when I try to get only
one column transformed
> test <- apply(chin.sub, chin.sub$density, log1p)
Error in apply(chin.sub, chin.sub$density, log1p) : 
        subscript out of bounds

I've tried using tapply:
> test <- tapply(chin.sub, chin.sub$density, log1p)
Error in tapply(chin.sub, chin.sub$density, log1p) : 
        arguments must have same length

Any advice on how to accomplish this?

On a related note how could I go about running the data frame
iteratively through a series of lm() statements without cutting and
pasting similar commands with diff variables or hardcoding the column
names?

e.g. do lm(x~y1)
	lm(x~y2)
	...
     end

Thanks in advance, Rob
> version
platform i386-pc-mingw32
arch     i386           
os       mingw32        
system   i386, mingw32  
status                  
major    1              
minor    6.0            
year     2002           
month    10             
day      01             
language R   
-- 
Rob Schick
Research Associate
NOAA Fisheries
Santa Cruz Lab
110 Shaffer Road
Santa Cruz, CA 95060
Phone: 831.420.3960
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On Thu, 14 Nov 2002, Robert Schick wrote:
> I have a 30 x 27 data frame, which I'm trying to scale and transform.
> Only I want to scale certain all variables except one (the dependent,
> which I want to log+1 transform). I can use split() and then scale() and
> log1p(), but I'm wondering if I can do this in one call.
>
> I tried apply(), but I could only get the whole data frame, not a part
> of it:
you want something like

test <- chin.sub
m <- match("density", names(test)
test[-m] <- scale(test[-m])
test$density <- log1p(test$density)
> On a related note how could I go about running the data frame
> iteratively through a series of lm() statements without cutting and
> pasting similar commands with diff variables or hardcoding the column
> names?
>
> e.g. do lm(x~y1)
> 	lm(x~y2)
Depends what you want to do with the results. E.g. add1 will add all
single variables and report the reduction in SSq etc.  Or something like

m <- names(DF)
m <- m[-match("x", m]
do.call(lm, lapply(paste("x ~", m), as.formula))

[untested]


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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