using filter() to sum up
On 04 May 2015, at 21:38 , T.Riedle <tr206 at kent.ac.uk> wrote:
Hi everybody, I am trying to create a code for the formula in the attachment. I first tried following code: ltau <- m + theta*sum(psi*X[t-k])
That's not going to work. It might work with something like sum(psi*X[(t-1):(t-K)])
but it does not work and I get for X[t-k] every third element in my vector three times which looks as follows: X[t-k] [1] -0.25 -0.25 -0.25 0.50 0.50 0.50 -0.44 -0.44 -0.44 0.15 0.15 0.15 Thus, I tried the filter() function in R which looks as follows: ltau <- m + theta* filter(f.USA$UTS, phi(K, omega1, omega2), sides=1, method="conv") Reading the description of this function I am unsure whether this provides the sum of the k lags. The appreviation "conv" provides, as far as I understand, the moving average instead of the sum.
I would assume that it means convolution. Which is what you have in the formula.
Does anybody have an idea how the R code for the formula attached must look like? Is the filter() function appropriate?
It's barking up the right tree, but do your own checks... -pd
Thanks in advance. <tau.png>______________________________________________
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Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com