Actually now that I read it closer, I see what your problem is. what
did you think the statement:
Preg[,k]<-coef(lm(tt~sel_col))
was going to do? Preg is a 200x100 matrix and you are only storing
two values (the coefficients) so they will be repeated 100 times in
the column. So there is nothing wrong with your nested "for" loops;
it is in the algorithm that you are using. You might want to use the
browser and you would see something like this:
Browse[1]> str(sel_col)
num [1:5] -0.115 -2.666 -0.811 1.440 -0.879
Browse[1]> str(tt)
Time-Series [1:5] from 2 to 10: 2 4 6 8 10
Browse[1]> n
debug: if (!all(is.na(sel_col))) {
Preg[, k] <- coef(lm(tt ~ sel_col))
}
Browse[1]> n
debug: Preg[, k] <- coef(lm(tt ~ sel_col))
Browse[1]> k
[1] 1
Browse[1]> n
debug: k
Browse[1]> n
debug: sel_col <- PmatWt[, k]
Browse[1]> k
[1] 2
Browse[1]> str(sel_col)
num [1:5] -0.115 -2.666 -0.811 1.440 -0.879
Browse[1]> str(Preg)
num [1:200, 1:100] 6.356 0.587 6.356 0.587 6.356 ...
Browse[1]> str(PmatWt)
num [1:5, 1:100] -0.115 -2.666 -0.811 1.440 -0.879 ...
Browse[1]> coef(lm(tt~sel_col))
(Intercept) sel_col
6.355760 0.586699
Browse[1]> str(Preg)
num [1:200, 1:100] 6.356 0.587 6.356 0.587 6.356 ...
Browse[1]>
This would help you to understand what is happening.
On Mon, Aug 4, 2008 at 8:35 PM, jim holtman <[EMAIL PROTECTED]> wrote:
> Exactly what problem are you having? There is nothing wrong with
> nested for loops, so what is leading you to believe you have a
> problem? I ran your program and it seems to terminate. Most of the
> time seems to have been spent in the following statement:
>
> if(!all(is.na(sel_col))) {Preg[,k]<-coef(lm(tt~sel_col))}
>
> Given that you appear to be executing this statement about 9000 times,
> it is not surprising. So can you provide more details?
>
> 0 51.2 root
> 1. 44.5 coef
> 2. . 44.1 lm
> 3. . . 15.7 eval
> 4. . . . 15.6 eval
> 5. . . . | 15.6 model.frame
> 6. . . . | . 15.3 model.frame.default
> 7. . . . | . . 6.0 sapply
> 8. . . . | . . . 3.8 lapply
> 9. . . . | . . . . 3.0 FUN
> 10. . . . | . . . . | 1.1 %in%
> 11. . . . | . . . . | . 1.0 match
> 12. . . . | . . . . | . . 0.8 is.factor
> 13. . . . | . . . . | . . . 0.7 inherits
> 10. . . . | . . . . | 1.0 .deparseOpts
> 11. . . . | . . . . | . 0.3 pmatch
> 9. . . . | . . . . 0.5 as.list
> 8. . . . | . . . 1.7 unique
> 9. . . . | . . . . 0.7 unique.default
> 9. . . . | . . . . 0.6 unlist
> 10. . . . | . . . . | 0.4 lapply
> 8. . . . | . . . 0.3 unlist
> 7. . . . | . . 4.0 na.omit
> 8. . . . | . . . 3.8 na.omit.data.frame
> 9. . . . | . . . . 3.0 [
> 10. . . . | . . . . | 2.9 [.data.frame
> 11. . . . | . . . . | . 0.6 duplicated
> 12. . . . | . . . . | . . 0.3 duplicated.default
> 11. . . . | . . . . | . 0.3 [
> 12. . . . | . . . . | . . 0.2 [.ts
> 11. . . . | . . . . | . 0.3 [[
>
> On Mon, Aug 4, 2008 at 12:58 PM, rcoder <[EMAIL PROTECTED]> wrote:
>>
>> Hi,
>>
>> I guess my question is really more about the nested for loop construct and
>> whether it is doing what I intend it to do in my code in the previous post.
>> I would be grateful if anyone who has used nested loops could let me know if
>> I am doing something wrong.
>>
>> Thanks,
>>
>> rcoder
>>
>>
>>
>> rcoder wrote:
>>>
>>> Hi everyone,
>>>
>>> I'm experiencing difficulty getting the results I want when I use a nested
>>> for loop. I have a data set to which I perform some calculations, and then
>>> try to apply a regression over a rolling window. The code runs, but the
>>> regression results I am getting (intercept and slope) are simply the same,
>>> repeated again and again in the results matrix. The regression does not
>>> seem to be obeying the instructions of the nested loop, which intend it to
>>> calculate regression coefficients over a data one row at a time. I have
>>> been struggling with the code for many days now, testing various parts,
>>> and I cannot seem to get the nested loop to work as I want it to. I would
>>> be very grateful for any suggestions. Below is a brief version of my code:
>>>
>>> #Code start
>>> library(zoo)
>>> seed.set(1)
>>> Pmat<-matrix(rnorm(1000), nrow=100, ncol=100)
>>> maxcol<-ncol(Pmat)
>>> maxrow<-nrow(Pmat)
>>> startrow<-10
>>> period<-10
>>> wind<-2 #roll window
>>> subdiv<-period/wind
>>> rollstart<-11 #start roll at period+1
>>> #converting Pmat into ts for rollapply() to work...
>>> PmatTS<-ts(Pmat)
>>> Preg<-matrix(NA,ncol=maxcol,nrow=2*maxrow)
>>> PmatWt<-matrix(NA, nrow=subdiv,ncol=maxcol)
>>> mult_col<-matrix(1:5, nrow=5, ncol=1)
>>> #rolling calculations...
>>> for (i in (rollstart):maxrow)
>>> {
>>> #extract the relevant timeframe...
>>> dslice<-PmatTS[(i-period):i,]
>>> dslicets<-ts(dslice)
>>> #operating on sliced data...
>>> Pmin<-rollapply(dslicets, wind, by=wind, min, na.rm=F)
>>> Pmax<-rollapply(dslicets, wind, by=wind, max, na.rm=F)
>>> Pmult<-Pmin*Pmax #calculating product
>>> tt<-time(Pmult)
>>> for (j in 1:5) #1st nested loop
>>> {
>>> PmatWt[j,]<-Pmult[j,]*mult_col[j,]
>>> }
>>> #rolling regression analysis...
>>> for (k in 1:maxcol) #2nd nested loop
>>> {
>>> sel_col<-PmatWt[,k]
>>> if(!all(is.na(sel_col))) {Preg[,k]<-coef(lm(tt~sel_col))}
>>> }
>>> }
>>> #Code End
>>>
>>> Thanks,
>>>
>>> rcoder
>>>
>>
>> --
>> View this message in context:
>> http://www.nabble.com/problem-with-nested-loop-for-regression-tp18792841p18815273.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
>
> --
> Jim Holtman
> Cincinnati, OH
> +1 513 646 9390
>
> What is the problem that you are trying to solve?
>
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem that you are trying to solve?
______________________________________________
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and provide commented, minimal, self-contained, reproducible code.
