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- W2122216747 abstract "In this paper we consider the problem of spectral estimation through ARMA modeling of stationary time series witch missing observations. We consider estimators based on the sample covariances, and present an asymptotically optimal estimator among this group. The algorithm is based on a nonlinear least squares fit of the sample covariances computed from the data with missing observations to the true covariances of the assumed ARMA model. The statistical properties of the algorithm are shown to be asymptotically optimal. The performance of the algorithm is illustrated by a numerical example." @default.
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- W2122216747 date "2005-03-24" @default.
- W2122216747 modified "2023-09-26" @default.
- W2122216747 title "ARMA parameter estimation based on sample covariances, for missing data" @default.
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- W2122216747 doi "https://doi.org/10.1109/icassp.1986.1169110" @default.
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