Least Absolute Deviation Estimation for All-Pass Time Series Models

@inproceedings{Davis2001LeastAD,
  title={Least Absolute Deviation Estimation for All-Pass Time Series Models},
  author={Richard A. Davis},
  year={2001}
}
An autoregressive-moving average model in which all of the roots of the autoregressive polynomial are reciprocals of roots of the moving average polynomial and vice versa is called an all-pass time series model. All-pass models generate uncorrelated (white noise) time series, but these series are not independent in the non-Gaussian case. An approximation to the likelihood of the model in the case of Laplace (two-sided exponential) noise yields a modi ed absolute deviations criterion, which can… CONTINUE READING
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