Compute parameter variability, plot confidence bounds

When you estimate the model parameters from data, you obtain their nominal values that are accurate within a confidence region. The size of this region is determined by the values of the parameter uncertainties computed during estimation. The magnitude of the uncertainties provide a measure of the reliability of the model. You can compute and visualize the effect of parameter uncertainties on the model response in time and frequency domains.

`present` |
Display model information, including estimated uncertainty |

`simsd` |
Simulate linear models with uncertainty using Monte Carlo method |

`freqresp` |
Frequency response over grid |

`rsample` |
Random sampling of linear identified systems |

`showConfidence` |
Display confidence regions on response plots for identified models |

`getcov` |
Parameter covariance of linear identified parametric model |

`setcov` |
Set parameter covariance data in identified model |

`translatecov` |
Translate parameter covariance across model operations |

`step` |
Step response plot of dynamic system; step response data |

`stepplot` |
Plot step response and return plot handle |

`impulse` |
Impulse response plot of dynamic system; impulse response data |

`bode` |
Bode plot of frequency response, magnitude and phase of frequency response |

`bodemag` |
Bode magnitude response of LTI models |

`nyquist` |
Nyquist plot of frequency response |

`nyquistplot` |
Nyquist plot with additional plot customization options |

`iopzmap` |
Plot pole-zero map for I/O pairs of model |

`iopzplot` |
Plot pole-zero map for I/O pairs and return plot handle |

`simsdOptions` |
Option set for simsd |

**Plot Impulse and Step Response Using the System Identification
App**

To create a transient analysis plot in the System Identification
app, select the **Transient resp** check box in the **Model
Views** area.

**Plot Bode Plots Using the System Identification App**

To create a frequency-response plot for linear models in the
System Identification app, select the **Frequency resp** check
box in the **Model Views** area.

**Plot the Noise Spectrum Using the System Identification App**

To create a noise spectrum plot for parametric linear models
in the app, select the **Noise spectrum** check box
in the **Model Views** area.

**Plot the Noise Spectrum at the Command Line**

To plot the disturbance spectrum of an input-output model or
the output spectrum of a time series model, use `spectrum`

.

**Model Poles and Zeros Using the System Identification App**

To create a pole-zero plot for parametric linear models in the
System Identification app, select the **Zeros and poles** check
box in the **Model Views** area.

Computing model parameter uncertainty of linear models.

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