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**Class: **dssm

Display summary information for diffuse state-space model

`disp(Mdl)`

`disp(Mdl,params)`

`disp(___,Name,Value)`

`disp(`

displays
summary information for the diffuse state-space model (`Mdl`

)`dssm`

model object) `Mdl`

.
The display includes the state and observation equations as a system
of scalar equations to facilitate model verification. The display
also includes the coefficient dimensionalities, notation, and initial
state distribution types.

The software displays unknown parameter values using `c1`

for
the first unknown parameter, `c2`

for the second
unknown parameter, and so on.

For time-varying models with more than 20 different sets of equations, the software displays the first and last 10 groups in terms of time (the last group is the latest).

`disp(___,`

displays `Name,Value`

)`Mdl`

using
additional options specified by one or more `Name,Value`

pair
arguments. For example, you can specify the number of digits to display
after the decimal point for model coefficients, or the number of terms
per row for state and observation equations. You can use any of the
input arguments in the previous syntaxes.

The software always displays explicitly specified state-space models (that is, models you create without using a parameter-to-matrix mapping function). Try explicitly specifying state-space models first so that you can verify them using

`disp`

.A parameter-to-matrix function that you specify to create

`Mdl`

is a black box to the software. Therefore, the software might not display complex, implicitly defined state-space models.

If you implicitly create

`Mdl`

, and if the software cannot infer locations for unknown parameters from the parameter-to-matrix function, then the software evaluates these parameters using their initial values and displays them as numeric values. This evaluation can occur when the parameter-to-matrix function has a random, unknown coefficient, which is a convenient form for a Monte Carlo study.The software displays the initial state distributions as numeric values. This type of display occurs because, in many cases, the initial distribution depends on the values of the state equation matrices

`A`

and`B`

. These values are often a complicated function of unknown parameters. In such situations, the software does not display the initial distribution symbolically. Additionally, if`Mean0`

and`Cov0`

contain unknown parameters, then the software evaluates and displays numeric values for the unknown parameters.

[1] Durbin J., and S. J. Koopman. *Time Series
Analysis by State Space Methods*. 2nd ed. Oxford: Oxford
University Press, 2012.

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