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ON THE EFFICIENCY OF THE SAMPLE MEAN IN LONG‐MEMORY NOISE
Author(s) -
Samarov Alexander,
Taqqu Murad S.
Publication year - 1988
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.1988.tb00463.x
Subject(s) - mathematics , estimator , efficiency , statistics , best linear unbiased prediction , series (stratigraphy) , sample mean and sample covariance , long memory , noise (video) , econometrics , volatility (finance) , selection (genetic algorithm) , paleontology , artificial intelligence , computer science , image (mathematics) , biology
. When estimating the unknown mean of a stationary time series, the best linear unbiased estimator is often a significantly better estimator than the ordinary least squares estimates X̄ n . The relative efficiency of these two estimators is investigated for time series whose spectrum behaves like a power at the origin (e.g., fractional Gaussian noise and fractional ARIMA).