Uniformly minimum variance nonnegative quadratic unbiased estimation in a generalized growth curve model

Consider the generalized growth curve model subject to R(Xm)[subset, double equals]...[subset, double equals]R(X1), where Bi are the matrices of unknown regression coefficients, and and are independent and identically distributed with the same first four moments as a random vector normally distributed with mean zero and covariance matrix [Sigma]. We derive the necessary and sufficient conditions under which the uniformly minimum variance nonnegative quadratic unbiased estimator (UMVNNQUE) of the parametric function with C>=0 exists. The necessary and sufficient conditions for a nonnegative quadratic unbiased estimator with of to be the UMVNNQUE are obtained as well.