RATS 11.1
RATS 11.1

Procedures /

ARMADLM Procedure

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@ARMADLM sets up the A and F matrices for a DLM based upon the ARMA model in an input equation. This can actually be an ARIMA equation: the state-space representation will then have some unit roots.

@ARMADLM(A=amat,F=fmat,C=Cmat,Z=Zvector) equation

Parameters

equation

The ARMA equation, which you can define with EQUATION or BOXJENK(DEFINE=...)

Options

A=(output) A matrix for input to DLM

F=(output) F matrix for input to DLM

C=(output) C matrix for input to DLM

Z=(output) Z vector for input to DLM

Description

The state space representation is from Jones(1980). The state-space representation uses a state vector consisting of

 

\({x_t},{x_{t + 1|t}},{x_{t + 2|t}}, \ldots {x_{t + r - 1|t}}\)

 

where \({x_{s|t}}\) is the linear predictor of x at s given information through t. For this model, \(\bf{A}\) takes the form

 

\(\left[ {\begin{array}{*{20}{c}}  0 & 1 & 0 &  \ldots  & 0  \\ 0 & 0 & 1 &  \ldots  & 0  \\ \vdots  &  \vdots  &  \ddots  &  \ddots  &  \vdots   \\ 0 & 0 &  \ldots  & 0 & 1  \\ {{\varphi _r}} & {{\varphi _{r - 1}}} &  \ldots  & {{\varphi _2}} & {{\varphi _1}}  \\ \end{array}} \right]\)

 

where the \(\phi\) are the AR coefficients. F is the vector of  "psi weights", that is, the responses of the model to a unit shock. The dimension \(r = \max (p,q + 1)\). The "C" matrix for this DLM is just (1,0,...,0). If there's a CONSTANT in the equation, the "Z" vector is (0,...,alpha).

Example

set dy = logy-logy{1}

boxjenk(ma=||2,4||,demean,maxl,define=dyeq) dy

compute bstart=%regstart(),bend=%regend()

*

* Save the extracted mean

*

compute dymean = %mean

*

* Convert the ARMA equation to a state-space representation

*

@armadlm(a=adlm,f=fdlm) dyeq

***********************************************************************************

*

* Random simulation can be done in a straightforward fashion using DLM

* with TYPE=SIMULATE.

*

dlm(type=simulate,presample=ergodic,a=adlm,f=fdlm,sw=%seesq) bstart bend xstates

 

This estimates an MA(2) with only the 2,4 lags, uses @ARMADLM to create the A and F for a state-space model and uses those to simulate a realization of that process.


 


Copyright © 2026 Thomas A. Doan