peOptions

Option set for pe

Syntax

opt = peOptions
opt = peOptions(Name,Value)

Description

opt = peOptions creates the default options set for pe.

opt = peOptions(Name,Value) creates an option set with the options specified by one or more Name,Value pair arguments.

Input Arguments

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

'InitialCondition'

Specify the handling of initial conditions.

InitialCondition takes one of the following:

  • 'z' — Zero initial conditions.

  • 'e' — Estimate initial conditions such that the prediction error for observed output is minimized.

  • 'd' — Similar to 'e', but absorbs nonzero delays into the model coefficients.

  • x0 — Numerical column vector denoting initial states. For multi-experiment data, use a matrix with Ne columns, where Ne is the number of experiments. Use this option for state-space and nonlinear models only.

  • io — Structure with the following fields:

    • Input

    • Output

    Use the Input and Output fields to specify the input/output history for a time interval that starts before the start time of the data used by pe. If the data used by pe is a time-series model, specify Input as []. Use a row vector to denote a constant signal value. The number of columns in Input and Output must always equal the number of input and output channels, respectively. For multi-experiment data, specify io as a struct array of Ne elements, where Ne is the number of experiments.

  • x0obj — Specification object created using idpar. Use this object for discrete-time state-space models only. Use x0obj to impose constraints on the initial states by fixing their value or specifying minimum/maximum bounds.

Default: 'e'

'InputOffset'

Removes offset from time domain input data during prediction-error calculation.

Specify as a column vector of length Nu, where Nu is the number of inputs.

For multi-experiment data, specify InputOffset as an Nu-by-Ne matrix. Nu is the number of inputs, and Ne is the number of experiments.

Each entry specified by InputOffset is subtracted from the corresponding input data.

Specify input offset for only time domain data.

Default: []

'OutputOffset'

Removes offset from time domain output data during prediction-error calculation.

Specify as a column vector of length Ny, where Ny is the number of outputs.

In case of multi-experiment data, specify OutputOffset as a Ny-by-Ne matrix. Ny is the number of outputs, and Ne is the number of experiments.

Each entry specified by OutputOffset is subtracted from the corresponding output data.

Specify output offset for only time domain data.

Default: []

'OutputWeight'

Weight of output for initial condition estimation.

OutputWeight takes one of the following:

  • [] — No weighting is used. This value is the same as using eye(Ny) for the output weight, where Ny is the number of outputs.

  • 'noise' — Inverse of the noise variance stored with the model.

  • matrix — A positive, semidefinite matrix of dimension Ny-by-Ny, where Ny is the number of outputs.

Default: []

Output Arguments

opt

Option set containing the specified options for pe.

Examples

expand all

Specify Options for Prediction-Error Calculation

Create an options set for pe using zero initial conditions, and set the input offset to 5.

opt = peOptions('InitialCondition','z','InputOffset',5);

Alternatively, use dot notation to set the values of opt.

opt = peOptions;
opt.InitialCondition = 'z';
opt.InputOffset = 5;

See Also

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