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forecastOptions

Option set for forecast

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Syntax

opt = forecastOptions
opt = forecastOptions(Name,Value)

Description

example

opt = forecastOptions creates the default option set for forecast. Use dot notation to modify this option set. Any options that you do not modify retain their default values.

example

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

Examples

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Open Live Script

Create a default option set for forecast. 

opt = forecastOptions;

Specify the input offset for a single-input data set as 5.

opt.InputOffset = 5;

You can now use this option set for forecasting. Before forecasting model response, the forecast command subtracts this offset value from the past input data signal.

Open Live Script

Create an option set for forecast using zero initial conditions.

opt = forecastOptions('InitialCondition','z');
Open Live Script

Load past measured data from two experiments.

load iddata1
load iddata2

z1 and z2 are iddata objects that store SISO input-output data. Create a two-experiment data set from z1 and z2.

z = merge(z1,z2);

Estimate a transfer function model with 2 poles using the multi-experiment data.

sys = tfest(z,2);

Specify the offset as -1 and 1 for the output signals of the two experiments.

opt = forecastOptions('OutputOffset',[-1 1]);

OutputOffset is specified as an Ny-by-Ne matrix where Ny is the number of outputs in each experiment, and Ne is the number of experiments. In this example, Ny is 1 and Ne is 2.

Using the option set opt, forecast the response of the model 10 time steps into the future. The software subtracts the offset value OutputOffset(i,j) from the output signal i of experiment j before using the data in the forecasting algorithm. The removed offsets are added back to generate the final result.

y = forecast(sys,z,10,opt)
y =
Time domain data set containing 2 experiments.

Experiment   Samples      Sample Time          
   Exp1          10            0.1             
   Exp2          10            0.1             
                                               
Outputs      Unit (if specified)               
   y1                                          
                                               
Inputs       Unit (if specified)               
   u1

y is an iddata object that returns the forecasted response corresponding to each set of past experimental data.

Input Arguments

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Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: forecastOptions('InitialCondition','e') specifies that the software estimates the initial conditions of the measured input-output data such that the 1-step prediction error for observed output is minimized.

Handling of initial conditions, specified as the comma-separated pair consisting of 'InitialCondition' and one of the following values:

  • 'z' — Zero initial conditions.

  • 'e' — Estimate initial conditions such that the 1-step prediction error is minimized for the observed output.

    For nonlinear grey-box models, only those initial states i that are designated as free in the model (sys.InitialStates(i).Fixed = false) are estimated. To estimate all the states of the model, first specify all the Nx states of the idnlgrey model sys as free.

    for i = 1:Nx
sys.InitialStates(i).Fixed = false;
end

    Similarly, to fix all the initial states to values specified in sys.InitialStates, first specify all the states as fixed in the sys.InitialStates property of the nonlinear grey-box model.

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

Input signal offset for time-domain data, specified as the comma-separated pair consisting of 'InputOffset' and one of the following values:

  • [] — No input offsets.

  • A column vector of length Nu, where Nu is the number of inputs. When you use the forecast command, the software subtracts the offset value InputOffset(i) from the ith input signals in the past and future input values. You specify these values in the PastData and FutureInputs arguments of forecast. The software then uses the offset subtracted inputs to forecast the model response.

  • Nu-by-Ne matrix — For multi-experiment data, specify InputOffset as an Nu-by-Ne matrix, where Ne is the number of experiments. The software subtracts the offset value InputOffset(i,j) from the ith input signal of the jth experiment in the PastData and FutureInputs arguments of forecast before forecasting.

Output signal offset for time-domain data, specified as the comma-separated pair consisting of 'OutputOffset' and one of the following values:

  • [] — No output offsets.

  • A column vector of length Ny, where Ny is the number of outputs. When you use the forecast command, the software subtracts the offset value OutputOffset(i) from the ith past output signal that you specify in the PastData argument of forecast. The software then uses the offset subtracted output to compute the detrended forecasts. The removed offsets are added back to the detrended forecasts to generate the final result.

  • Ny-by-Ne matrix — For multi-experiment data, specify OutputOffset as an Ny-by-Ne matrix, where Ne is the number of experiments. Before forecasting, the software subtracts the offset value OutputOffset(i,j) from the ith output signal of the jth experiment in the PastData argument of forecast. For an example, see Specify Output Offset for Forecasting Multi-Experiment Data.

Output Arguments

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Option set for forecast, retuned as a forecastOptions option set.

Version History

Introduced in R2012a

See Also

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