[R] Re gression between adjacent columns - error with NAs
rcoder
mpdotbook at gmail.com
Wed Jul 30 23:54:02 CEST 2008
Hi Gabor,
Thanks for your reply. I've written something that can be copied and pasted
into your monitor to reproduce the error I am experiencing. Once the loop
experiences a column full of NAs in SourceMat (column 3), it exits with
errors, and ResultMat is only partially complete (up to column 2) with o/p
intercept and slope results.
When I include the 'na.action=NULL' statement, I get the following
statement:
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
NA/NaN/Inf in foreign function call (arg 1)
When I leave this statement out, I get the following:
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
0 (non-NA) cases
In either case, ResultMat is only filled up to column 2:
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5.3611056 5.4099400 NA NA NA NA NA NA NA NA
[2,] -0.8028985 -0.4078084 NA NA NA NA NA NA NA NA
##Code start
SourceMat<-matrix(data=rnorm(100), ncol=10, nrow=10)
SourceMat[,3]<-c(NA)
tt<-time(SourceMat)
rownum=2
colnum=10
ResultMat<-matrix(NA, ncol=colnum, nrow=rownum)
#loop through each column in the source matrix:
for (i in 1:10)
{
sel_col<-SourceMat[col(SourceMat)==i] #selecting the correct column
in the matrix in turn
ResultMat[,i]<-coef(lm(tt~sel_col, na.action=NULL))
}
##Code end
I would be grateful for any suggestions to avoid this problem.
Thanks,
rcoder
rcoder wrote:
>
> 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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>>
>> ______________________________________________
>> R-help at r-project.org mailing list
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>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
>
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