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Estimation of variances in orthogonal finite discrete spectrum linear regression models

Author

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  • František Štulajter
  • Viktor Witkovský

Abstract

The Invariant Quadratic Estimators, the Maximum Likelihood Estimator (MLE) and Restricted Maximum Likelihood Estimator (REML) of variances in an orthogonal Finite Discrete Spectrum Linear Regression Model (FDSLRM) are derived and the problems of unbiasedness and consistency of these estimators are investigated. Copyright Springer-Verlag 2004

Suggested Citation

  • František Štulajter & Viktor Witkovský, 2004. "Estimation of variances in orthogonal finite discrete spectrum linear regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 60(2), pages 105-118, September.
    • Handle: RePEc:spr:metrik:v:60:y:2004:i:2:p:105-118
    DOI: 10.1007/s001840300299
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    Cited by:

    1. Martina Hančová & Andrej Gajdoš & Jozef Hanč & Gabriela Vozáriková, 2021. "Estimating variances in time series kriging using convex optimization and empirical BLUPs," Statistical Papers, Springer, vol. 62(4), pages 1899-1938, August.

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