From: mkondrin <mkondrin_at_hppi.troitsk.ru>

Date: Thu 02 Jun 2005 - 02:31:35 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Jun 02 02:43:28 2005

Date: Thu 02 Jun 2005 - 02:31:35 EST

Thank you very much for clearing my question (for me too ;)) The model I would like to fit is :

X_t = phi_1 * X_{t-1} + phi_2 * X_{t-2}

+ phi_3 * X_{t-3} +A_1*f_{t-1}+A_2*f_{t-2}...+A_k*f_{t-k} + E_t (*)

(X_t and f_t time series are both known, k - fixed and more than 1).
lm is a good answer (I surely try it), but I thought may be somethere in
R exists a front-end to lm for this particular case. For example if I
have a model

X_t = phi_1 * X_{t-1} + phi_2 * X_{t-2}

+ phi_3 * X_{t-3} + E_t (**), I would usean "ar" command from "stats" package. My problem is how to make my model (*) suit "ar" command (may model (*) be rewritten in (**) form)?

Rolf Turner wrote:

>It is not at all clear what you want to do. One conjecture

*>(attempt at reading your mind):
**>
**> X_t = ``black box's state'' at time t
**> f_t = ``force'' at time t
**>
**> Proposed model e.g. AR(3):
**>
**> X_t = phi_1 * X_{t-1} + phi_2 * X_{t-2}
**> + phi_3 * X_{t-3} + f_t
**>
**> You wish to identify/estimate the coefficients phi_1, phi_2,
**> phi_3.
**>
**>Remarks:
**>
**> (a) This model probably doesn't make a lot of sense, with
**> known/observed f_t. It will almost surely not hold exactly,
**> for ***any*** values of the phi_i.
**>
**> (b) A model which makes a bit more sense, in the abstract, is
**>
**> X_t = phi_1 * X_{t-1} + phi_2 * X_{t-2}
**> + phi_3 * X_{t-3} + f_t + E_t
**>
**> where E_t is (unobserved) i.i.d. random ``error''.
**>
**> (c) This last model is just a simple regression model and
**> may be fitted using lm().
**>
**> cheers,
**>
**> Rolf Turner
**> rolf@math.unb.ca
**>
**>Original message:
**>
**>
**>
**>>Hello!
**>>Is it possible to use R time series to identificate a process which is
**>>subjected to known input? I.e. I have 2 sequences - one is measurements
**>>of black box's state and the second is the "force" by which this black
**>>box is driven (which is known too) and I want to fit thist two series
**>>with AR-process. The "ar" procedure from stats package expects that the
**>>force is always random. Is it possible to feed it known vector as input
**>>parameter?
**>>Thank you in advance.
**>>
**>>
**>
**>______________________________________________
**>R-help@stat.math.ethz.ch mailing list
**>https://stat.ethz.ch/mailman/listinfo/r-help
**>PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
**>
**>
*

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Jun 02 02:43:28 2005

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