Characterization of the multivariate Gauss-Markoff model with singular covariance matrix and missing values

Oktaba, Wiktor

Applications of Mathematics, Tome 43 (1998) no. 2, pp. 119-131.

Résumé

The aim of this paper is to characterize the Multivariate Gauss-Markoff model $(MGM)$ as in () with singular covariance matrix and missing values. $MGMDP2$ model and completed $MGMDP2Q$ model are obtained by three transformations $D$, $P$ and $Q$ (cf. ()) of $MGM$. The unified theory of estimation (Rao, 1973) which is of interest with respect to $MGM$ has been used. The characterization is reached by estimation of parameters: scalar $\sigma ^{2}$ and linear combination $\lambda ^{\prime }\bar{B}$ ( $\bar{B}=vecB)$ as in (), (), () as well as by the model of the form () (cf. Th. ). Moreover, testing linear hypothesis in the available model $MGMDP2$ by test function $F$ as in () and () is considered. 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). An algorithm and the $UMGMBO$ program for calculations concerning estimation and testing in $MGM$ have been presented by Oktaba and Osypiuk (1993).

Détail

DOI : 10.1023/A:1023215001376

Classification : 62H05, 62J05
Keywords: multivariate Gauss-Markoff model; missing value; developed model; available model; completed model; elementary transformation; BLUE; estimation; testing; consistency; invariant