On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean *

@inproceedings{YinWong1991OnML,
  title={On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean *},
  author={Yin-Wong and D. Cheung},
  year={1991}
}
There are two approaches to maximum likelihood (ML) estimation of the parameter of fractionallyintegrated noise: approximate frequency-domain ML [Fox and Taqqu (1986)] and exact timedomain ML [Sowell (1992b)]. If the mean of the process is known, then a clear finite-sample mean-squared error ranking of the estimators emerges: the exact time-domain estimator is superior. We show in this paper, however, that the finite-sample efficiency of approximate frequency-domain ML relative to exact time… CONTINUE READING

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