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Polynomial Model Estimation Algorithms

For linear ARX and AR models, you can choose between the ARX and IV algorithms. ARX implements the least-squares estimation method that uses QR-factorization for overdetermined linear equations. IV is the instrument variable method. For more information about IV, see the section on variance-optimal instruments in System Identification: Theory for the User, Second Edition, by Lennart Ljung, Prentice Hall PTR, 1999.

The ARX and IV algorithms treat noise differently. ARX assumes white noise. However, the instrumental variable algorithm, IV, is not sensitive to noise color. Thus, use IV when the noise in your system is not completely white and it is incorrect to assume white noise. If the models you obtained using ARX are inaccurate, try using IV.


AR models apply to time-series data, which has no input. For more information, see Time Series Analysis. For more information about working with AR and ARX models, see Input-Output Polynomial Models.

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