Abstract:
Let
Y=
X1BX'2+
Uε,E
ε=0,be a multivariate linear model, where
X1 and
BX'2 are known matrics,
B is an unknown matrix and e is a random matrix. Assume that
ε=(
ε1,…,
εn)',\vec\epsilon=\widehat=\left(\varepsilon_1^\prime, \cdots, \varepsilon_n^\prime\right)^\prime and\mathrmE(\vec\varepsilon \vec\varepsilon)=I \otimes \Sigma, where \Sigma \geq 0 is an unknown covariance matrix. This paper gives a sufficient and necessary condition for \vecY^\prime(
MAM)\vecY to be the uniformly minimum variance invariance quadratic unbased estimation (UMVIQUE) of tr(
CΣ), where M=I-X_1 X_1^+ \otimes X_2 X_2^+ and
C≠0 is an arbitrary symmetric matrix. As corollary, the sufficient and necessary conditions for UMVIQUE of tr(
CΣ) to be exist and tr(
CΣ
*) to be the UMVIQUE of it(
CΣ) are given.