[ADMB Users] Linear multivariate state-space model.
John Sibert
sibert at hawaii.edu
Wed Jul 3 17:44:23 PDT 2013
Hi Dan,
There are some usefule materials to get started with state-space models
in ADMB. Chapter 8 of the ADMB manual describes implementation of a
simple Kalman filter. Anders Nielsen and I have developed various
state-space models for tracking data
http://www.soest.hawaii.edu/PFRP/reprints/Nielsen_Sibert_2007.pdf.
Regards,
John Sibert
John Sibert
Emeritus Researcher, SOEST
University of Hawaii at Manoa
Honolulu HI (GMT-10)
808-294-3842
Visit the ADMB project http://admb-project.org/
On 07/03/2013 08:15 AM, H. Skaug wrote:
> Hi Dan,
>
> Since your model is linear there are at least two approaches you can take:
> 1. Implement the Kalman filter (see chapter 8 in the ADMB manual)
> 2. Use the random effects module of ADMB in which you explicitly define
> your state variable X to be a latent variable. This approach
> can be generalized to nonlinear models.
>
> I recommend doing both as an exercise to understand the possibilities
> that ADMB offers. With regard to 2) there are a few tricks that people
> have tpl-files for.
>
> What is the size of your model, i.e. the dimension of X and the length
> of your
> time series? This info is critical for assessing which of 1 and 2 (if
> any) is
> the best choice. You say "spatio" which indicates that X is high
> dimentional.
>
> Hans
>
>
> On Wed, Jul 3, 2013 at 6:34 PM, Dan Gladish <dan.gladish at gmail.com
> <mailto:dan.gladish at gmail.com>> wrote:
>
> Hello all,
>
> I am currently working on a spatio-temporal model that we are
> hoping to implement in ADMB. Unfortunately, I am very new at ADMB
> and am looking for a little help. Specifically, I am looking to
> see if there are any examples of code for a multivariate linear
> state-space model:
>
> Y(t) = X(t) + e(t), e(t) \sim N(0,s2e I)
> X(t) = M*X(t-1) + eta(t), eta(t) \sim N(0,Q)
>
> where Y(t) is the data vector, X(t) is the latent variable vector,
> M is the propagator matrix, and s2e and Q the innovation variance
> and latent covariance, respectively.
>
> There are a few examples of state-space models, but I did not see
> one using a very bare bones set-up like this. Any help would be
> much appreciated for a lowly beginner like me.
>
> Sincerely,
> Dan Gladish
>
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