Kubáčková, Ludmila The locally best estimators of the first and second order parameters in epoch regression models. (English) Zbl 0743.62057 Appl. Math., Praha 37, No. 1, 1-12 (1992). Summary: In a linear epoch regression model the locally best linear unbiased estimators of the first order parameters and the locally minimum variance quadratic unbiased and invariant estimators of an unbiasedly and invariantly estimable linear function of the second order parameters in the \(j\)th epoch and after the \(j\)th epoch are derived. The algorithms mentioned utilize the special block structure of the model and the sparseness of the covariance matrix of the observation vector. Cited in 3 Documents MSC: 62J05 Linear regression; mixed models 62H12 Estimation in multivariate analysis 65C99 Probabilistic methods, stochastic differential equations Keywords:linear epoch regression model; locally best linear unbiased estimators; first order parameters; locally minimum variance quadratic unbiased and invariant estimators; estimable linear function; second order parameters; algorithms; block structure; sparseness of the covariance matrix × Cite Format Result Cite Review PDF Full Text: DOI EuDML References: [1] Lubomír Kubáček: Foundations of Estimation Theory. Elsevier, Amsterdam, Oxford, New York, Tokyo, 1988. · Zbl 0698.62004 [2] Lubomír Kubáček: Special structures of mixed linear model with nuisance parameters. Math. Slovaca 40 (1990), 191-207. · Zbl 0745.62071 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. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.