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I'm using the following code taken from MATLAB documentation to estimate the parameters of an ARMA model:

y = sin([1:300]') + 0.5 * randn(300, 1);
y = iddata(y);
mb = ar(y, 4, 'burg');

At this point, if if I type mb what I get is this:

Discrete-time IDPOLY model:
A(q)y(t) = e(t)
A(q) = 1 - 0.2764 q^-1 + 0.2069 q^-2 + 0.4804 q^-3 + 0.1424 q^-4
Estimated using AR ('burg'/'now') from data set y
Loss function 0.314965 and FPE 0.323364
Sampling interval: 1

How can I use the variable mb I obtained to generate samples with those coefficients?
mb doesn't look like a vector.
In particular, how can I handle missing data?

Amro
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Bob
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1 Answers1

2

Use: sim(mb,input)

More info about sim and also here:

Simulate linear models.

Syntax

y = sim(m,ue)

[y, ysd] = sim(m,ue,init)

Description

m is an arbitrary idmodel object.

ue is an iddata object, containing inputs only. The number of input channels in ue must either be equal to the number of inputs of the model m, or equal to the sum of the number of inputs and noise sources (= number of outputs). In the latter case the last inputs in ue are regarded as noise sources and a noise-corrupted simulation is obtained. The noise is scaled according to the property m.NoiseVariance in m, so in order to obtain the right noise level according to the model, the noise inputs should be white noise with zero mean and unit covariance matrix. If no noise sources are contained in ue, a noise-free simulation is obtained.

abdulhaq-e
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