Estimating State-Space Time-Series Models
Definition of State-Space Time-Series Model
The discrete-time state-space model for a time series is given
by the following equations:
where T is the sampling interval and y(kT) is
the output at time instant kT.
The time-series structure corresponds to the general structure
with empty B and D matrices.
For information about general discrete-time and continuous-time
structures for state-space models, see What Are State-Space Models?.
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Estimating State-Space Models at the Command Line
You can estimate single-output and multiple-output state-space
models at the command line for time-domain and frequency-domain data
(iddata object).
The following table provides a brief description of each command.
The resulting models are idss model
objects.
Commands for Estimating State-Space Time-Series Models
| Command | Description |
|---|
| n4sid | Noniterative subspace method for estimating discrete-time
linear state-space models. Note
When you use pem to estimate a state-space
model, n4sid creates the initial model. |
|
| pem | Estimates linear, discrete-time time-series models using
an iterative estimation method that minimizes the prediction error. |
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 | Estimating AR and ARMA Models | | Example – Identifying Time-Series Models at the Command
Line |  |
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