Message-ID: <3B6A60F0-7CB7-4ECF-A675-CEC6FF0962CC@gmail.com>
Date: 2015-05-05T09:40:56Z
From: Peter Dalgaard
Subject: using filter() to sum up
In-Reply-To: <AEB16B1613D44C4793A7E6B6986B7A12F536F21C@EX10-LIVE-MBN2.ad.kent.ac.uk>
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