Abstract
In this article, we consider an inference for a covariance matrix under two-step monotone incomplete sample. The maximum likelihood estimator of the mean vector is unbiased but that of the covariance matrix is biased. We derive an unbiased estimator for the covariance matrix using some fundamental properties of the Wishart matrix. The properties of the estimators are investigated and the accuracies are checked by a numerical simulation.
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Appendix A. Calculation of Asymptotic Covariance Matrix of the Estimator
In this section, we calculate the asymptotic covariance matrix for the MLE. Applying (Equation10(10) ), (Equation11(10) ), and (Equation12(10) ), we obtain the asymptotic covariance matrices as follows: