Wiktor Oktaba, Institute of Applied Mathematics, Department of Mathematical Statistics, Agricultural University, Akademicka 13, 20-934 Lublin, Poland, e-mail sek314@ursus.ar.lublin.pl
Abstract: The aim of this paper is to characterize the Multivariate Gauss-Markoff model $(MGM)$ as in (\ref{dwa1}) with singular covariance matrix and missing values. $MGMDP2$ model and completed $MGMDP2Q$ model are obtained by three transformations $D$, $P$ and $Q$ (cf. (\ref{trzy22})) of $MGM$. The unified theory of estimation (Rao, 1973) which is of interest with respect to $MGM$ has been used. \endgraf The characterization is reached by estimation of parameters: scalar $\sigma^2$ and linear combination $\lambda^{\prime}\bar{B}$ ( $\bar{B}=vecB)$ as in (\ref{cztery8}), (\ref{cztery6}), (\ref{cztery7}) as well as by the model of the form (\ref{piec1}) (cf. Th. \ref{tw51}). Moreover, testing linear hypothesis in the available model $MGMDP2$ by test function $F$ as in (\ref{szesc3}) and (\ref{szesc4}) is considered. \endgraf It is known (Oktaba 1992) that ten quantities in models $MGMDP2$ and $MGMDP2Q $ are identical (invariant). They permit to say that formulas for estimation and testing in both models are identical (Oktaba et al., 1988, Baksalary and Kala, 1981, Drygas, 1983). \endgraf An algorithm and the $UMGMBO$ program for calculations concerning estimation and testing in $MGM$ have been presented by Oktaba and Osypiuk (1993).
Keywords: multivariate Gauss-Markoff model, missing value, developed model, available model, completed model, elementary transformation, BLUE, estimation, testing, consistency, invariant
Classification (MSC 1991): 62H05
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