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transfer function-noise modelling in R

Cross Validated Asked by stucash on December 29, 2021

I recently started to learn transfer-function model, which, more specifically, is transfer-function-noise model(TFN). I have also attempted modeling it in R.

I found one thing that is baffling.

according to Tsay(2009) Lecture notes, Montgomery et al(2015), and Bisgaard et al(2011), in practice, the transfer function Model comes with innovations (the noise term). However if I understand correctly, the arima/arimax function from R package TSA does not provide an argument to account for the ARIMA noise term. e.g. they provide xtransf and transfer to help formulate the transfer function itself, but nothing for modeling the noise term which is normally taken to follow ARIMA.

Do they just not model the noise term like I said or I missed a critical part?

Or, they are taking the original data as an ARIMA noise series and model it with arimax and use the transfer function arguments to model the change in mean function (Cryer, 2008)? Cryer(2008) has presented the intervention analysis model, which is suitably derived from transfer funciton-noise model, as:

$Y_{t} = m_{t} + N_{t}spacespacespace (1)$

a more TFN-alike representation of $(1)$ is from Montgomery(2015):

$y_{t} = frac{w(B)}{delta(B)}xi_{t}^T + frac{theta(B)}{phi(B)}epsilon_{t} = v(B)xi_{t}^T + N_{t}$

In intervention analysis $xi_{t}^T$ is just a dummy/indicator variable.

One Answer

I have not and would not use the software you mention BUT if I had no choice .......

As you intimate they are not allowing for explicit incorporation of the model for the error term . In sympathy for the authors they are assuming the you the ma/ar structure and multiply both the Y and the X and voila you have a white noise error term as the model for the original noise term is now non-parsimoniously implicit in the expanded Y and X coefficients.

You asked if I knew of a piece of software that was VERY general in this area. I have helped develop this it is called AUTOBOX http://www.autobox.com and follows How to predict the next number in a series while having additional series of data that might affect it? . It also has an automatic model detection feature which includes intervention detection . https://autobox.com/capable.pdf is a useful introduction. It is available in R .

Answered by IrishStat on December 29, 2021

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