[R] Multiple linear regression with for loop

[bartjoosen]

I'm not sure if this is what you want but if you have a matrix as response,
you can use the matrix ~ term:
example:
x <- 1:10
y <- rep(rnorm(10,x,0.5),10)
dim(y) <- c(10,10)
y <- as.matrix(y)
coef(lm(y~x))


Bart


Markus &quot;Mühlbacher&quot; wrote:
> 
> Hi everyone!
> 
>  I have an array containing the following fields for over hundred
> compounds:
> cpd, activity, fixterm, energy1, energy2, energy3, ...
> 
> I want to run a multiple linear regression on all entries of an array.
> Therefore I tried to do this with a for loop. (Maybe there is a direct way
> of calculating it using apply, but I don't know that either.)
>  
>  Actually i tried the following code:
>  
>  ...
>  > attach(data)
>  > for(i in 1:length(cpd)) {
>  > fitted.model <- lm(activity ~ fixterm + i)
>  > coef(fitted.model)
>  > }
>  ...
>  
>  Unfortunatly this loop doesn't give the intended correlation coefficients
> of each regression. If I insert a line "print(i)" into the loop the
> desired values for i are printed correctly. Only the coefficient outputs
> are missing.
>  Probably the solution is very near, but I just can't see it.
>  
>  Many thanks in advance,
>  Markus
>  
>        
> ---------------------------------
> 
> 	[[alternative HTML version deleted]]
> 
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