R help - Jan 2008 - Sliding Window Time Series Analysis - hourly rainfall

I have a time series of rainfall in a dataframe.  I would like to be
able to aggregate this using a sliding window approach- i.e. a new 24
hourly total is calculated for each hours rainfall.  I'm struggling to
understand how this might be achieved - currently I've tried looping a
sum function to re-calculate a new total at every stage of the loop.

for (inp[[9]] in 1:length(inp[[9]])){data.frame(x<-sum(inp[y:y+24,9]))}

where inp is the data frame object and [[9]] is the column containing
rainfall.
y is used to try and get the previous 24 hours total however in it's
current state it seems useless.

If anyone could give me some pointers i'd be very pleased, I'm a bit new
to the R language so any help appreciated.
Thanks
Jamie Ledingham

Take a look at "filter" for doing a moving average.

On Jan 24, 2008 6:48 AM, Jamie Ledingham
<jamie.ledingham at newcastle.ac.uk> wrote:
> I have a time series of rainfall in a dataframe.  I would like to be
> able to aggregate this using a sliding window approach- i.e. a new 24
> hourly total is calculated for each hours rainfall.  I'm struggling to
> understand how this might be achieved - currently I've tried looping a
> sum function to re-calculate a new total at every stage of the loop.
>
> for (inp[[9]] in 1:length(inp[[9]])){data.frame(x<-sum(inp[y:y+24,9]))}
>
> where inp is the data frame object and [[9]] is the column containing
> rainfall.
> y is used to try and get the previous 24 hours total however in it's
> current state it seems useless.
>
> If anyone could give me some pointers i'd be very pleased, I'm a
bit new
> to the R language so any help appreciated.
> Thanks
> Jamie Ledingham
>
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>


-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem you are trying to solve?