Hi all,
How can a multivariate Poisson time series be modeled? Aspects of glm,
forecast, dse and dynlm seem relevant but not quite complete--but hopefully
what I am missing is how to assemble them effectively. What I am looking to
do is model my dependent variable y_t as a Poisson family functi
Hello Erin,
have you considered the package bundle "dse" on CRAN?
Best,
Bernhard
>
>Dear R People:
>
>I was looking to see if there are any functions for Vector
>ARMA modeling.
>
>I found Vector AR(p) but no Vector ARMAs.
>
>Thanks,
>Erin
>
>
>--
>Erin Hodgess
>Associate Professor
>Department
Dear R People:
I was looking to see if there are any functions for Vector ARMA modeling.
I found Vector AR(p) but no Vector ARMAs.
Thanks,
Erin
--
Erin Hodgess
Associate Professor
Department of Computer and Mathematical Sciences
University of Houston - Downtown
mailto: [EMAIL PROTECTED]
Thank you very much for your answers,you are all very kind!Excuse me, can I
make another question about time series?
When I use arimaId or best.arima function in package forecast, I can't
insert regressors, I can insert them only when I make predictions..
But isn't the model influenced by regresso
Hello to everyone, thank you for your answers, you are all very kind!
I'll have a look to the package you advised me.
Paul, I saw dse package, but I didn't understand how to use it..
For example, I have 2 sales series:
item_1 item_2 price_item1 price_item2
0 0 26
Package dse does do linear, multivariate time series with multivariate
exogenous inputs, using VAR, multivariate ARMA, and state-space models,
just like you are describing. You can specify the model or have it
automatically determined. Perhaps you could give a few more details
about what you ar
Giusy,
There is also a package "dlm" that may be useful, but you need to
specify the model you want to use.
Giovanni
> Date: Sun, 11 Nov 2007 08:40:42 -0800 (PST)
> From: Giusy <[EMAIL PROTECTED]>
> Sender: [EMAIL PROTECTED]
> Precedence: list
>
>
> Hello to everyone!
> I have a question for
Hello Giusy,
in addition to Frank's suggestion you might want to specify and estimate
a VECM (function ca.jo() in package urca). This object can be
transformed to its level-VAR representation (function vec2var() in
package vars) for which a predict-method exists (fan charts can be
generated too).
You may want to have a look at the vars package
Frank
Giusy schrieb:
> Hello to everyone!
> I have a question for you..I need to predict multivariate time series, for
> example sales of 2 products related one to the other, having the 2 prices
> like inputs..
> Is there in R a function to do it? I
U might look at Vector Auto regression model. Try library(mAr)
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Giusy
Sent: Sunday, November 11, 2007 10:11 PM
To: r-help@r-project.org
Subject: [R] Multivariate time series
Hello to everyone!
I have a
Hello to everyone!
I have a question for you..I need to predict multivariate time series, for
example sales of 2 products related one to the other, having the 2 prices
like inputs..
Is there in R a function to do it? I saw dse package but I didn't find what
a I'm looking for..
Could anyone help me
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