On Wed, Jul 11, 2012 at 10:05 AM, Russell Bowdrey
<russell.bowd...@justretirement.com> wrote:
>
> Dear all,
>
> This is what I'd like to do (I have an implementation using for loops, which
> I designed before I realised just how slow R is at executing them - this
> process currently takes days to run).
>
> I have a large dataframe containing corporate bond data, columns are:
> BondID
> Date (goes back 5years)
> Var1
> Var2
> Term2Maturity
>
> What I want to do is this:
>
> 1) For each bond, at each given date, look back over 1 year and append
> some statistics to each row ( sd(Var1), cor(Var1,Var2) over that year etc)
>
Look at the TTR package and the various run** functions. Much faster.
> a. It seems I might be able to use ddply for this, but I can't work out
> how to code the stats function to only look back over one year, rather than
> the full data range
>
> b. For example: dfBondsWithCorr<-ddply(dfBonds, .(BondID),
> transform,corr=cor(Var1,Var2),.progress="text")
> returns a dataframe where for each bond it has same corr for each date
>
> 2) On each date, subset dfBondsWithCorr by certain qualification
> criteria, then to the qualifiers fit a regression through a Var1 and
> Term2Maturity, output the regression as a df of curves (say for each date, a
> curve represented by points every 0.5 years)
>
> a. I can do this pretty efficiently for a single date (and I suppose I
> could wrap that in a function) , but can't quite see how to do the filtering
> and spitting out of curves over multiple dates without using for loops
>
This ones harder. For simple linear regressions, you can solve the
regression analytically (e.g., slope = runCov / runVar and mean
similarly) but doing it for more complicated regressions will pretty
much require a for loop of one sort or another. Can you say what sort
of model you are looking to use?
Best,
Michael
> Would appreciate any thoughts, many thanks in advance
>
>
> Russ
>
>
>
> This email and any attachments are confidential and inte...{{dropped:30}}
>
> ______________________________________________
> 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.
______________________________________________
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.
