As I said before: please dput() some working data and I'll try to work
something up.
Without it, the only thing I can reasonably suggest is that perhaps
you are looking for the window() function to be applied before
min/max. Something like:
X <- ts(1:48, start = 1, frequency = 4)
Y <- ts(1:12, st
Hello Michael,
Thanks again for your reply. Actually, I am working with wind data.
I have some sample data for actual load.
scan("/home/sam/Desktop/tt.dat") ->tt ## This is the input for the actual
output of the generation
t = ts(tt, start=8, end=24, frequency=1,)
I have another random sequen
Can you post working examples of your data using the dput() function?
There are so many types of time series in R and so many different
things you could mean that it's just easier to work with real data.
Michael
On Tue, Nov 15, 2011 at 4:28 PM, Sarwarul Chy wrote:
> Hello Michael,
> Thanks for y
Hello Michael,
Thanks for your reply. What I want to do is something like this? For
example, I have a continuous time series y=x(t), and another discrete time
series z=w(t).
Xdiff(i)=Max. difference between x(t) and w(t) in interval i
Ndiff(i)=Min. difference between x(t) and w(t) in interval
It's not clear what it means for the differences to be "of increasing
order" but if you simply mean the differences are increasing, perhaps
something like this will work:
library(caTools)
X = cumsum( 2*(runif(5e4) > 0.5) - 1) # Create a random Walk
Y = runmean(X, 30, endrule = "mean", align = "rig
Hello,
Can you please help me with this? I am also stack in the same problem.
Sam
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