[R] rolling regression between adjacent columns

[rcoder]

Well, in this case I don't think my original code would have helped much...

So, I've rewritten as below. I want to perform regression between one column
in a matrix and all other columns in the same matrix. I have a for loop to
achieve this, which succeeds in exporting intercept and slope coefficients
to a results matrix, except when a column that contains only NAs is reached.
Columns partially filled with NAs are handled, but the code exits with
errors when a single column is filled with NAs. I inserted the
'na.action=NULL' statement within the lm() construct, but to no avail. I
would be very grateful for any advice.

>tt<-time(SourceMat) 
>ResultMat<-matrix(NA, ncol=colnum, nrow=rownum)     #creates an o/p
template matrix 

#loop through each column in the source matrix: 
>for (i in 1:5000) 
                { 
        sel_col<-[col(SourceMat)==i] #selecting the correct column in the
matrix in turn 
        SourceMat[,i]<-coef(lm(tt~sel_col), na.action=NULL) 
                }

Thanks,

rcoder


Gabor Grothendieck wrote:
> 
> Read the last line of every message to r-help.
> 
> On Tue, Jul 29, 2008 at 6:15 PM, rcoder <mpdotbook at gmail.com> wrote:
>>
>> Hi everyone,
>>
>> I am trying to apply linear regression to adjacent columns in a matrix
>> (i.e.
>> col1~col2; col3~col4; etc.). The columns in my matrix come with
>> identifiers
>> at the top of each column, but when I try to use these identifiers to
>> reference the columns in the regression function using rollapply(), the
>> columns are not recognised and the regression breaks down. Is there a
>> more
>> robust way to reference the columns I need, so that I can apply the
>> regression across the matrix; 'by.column', but every other column?
>>
>> Thanks,
>>
>> rcoder
>> --
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> 
> ______________________________________________
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> 
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