Best estimator of the regression parameter in a reversing model. (English) Zbl 1267.62090

J. Sov. Math. 60, No. 4, 1615-1619 (1992); translation from Vychisl. Prikl. Mat., No. 60, 94–99 (1986).
Summary: A mathematical model of data processing for frequency sensors is proposed. The minimum-variance linear unbiased estimator of the constant signal is determined in the presence of “white noise ” and unknown non-stochastic drift by reversal of observations. The reversal time is taken into account. It is shown that if the drift is from a finite-dimensional space, and the estimation process reduces to solving a system of linear equations. An example is considered.


62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62M09 Non-Markovian processes: estimation
Full Text: DOI


[1] V. M. Alekseev, V. M. Tikhomirov, and S. V. Fomin, Optimal Control [in Russian], Nauka, Moscow (1979). · Zbl 0516.49002
[2] A. V. Balakrishnan, Applied Functional Analysis [Russian translation], Nauka, Moscow (1980).
[3] S. M. Zel’dovich, M. I. Maltinskii, I. M. Okon, and Ya. G. Ostromukhov, Self-Compensation of Instrumental Errors in Gyrosystems [in Russian], Sudostroenie, Leningrad (1976).
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.