Asymptotic expansions relating to discrimination based on two-step monotone missing samples

作者：Shutoh Nobumichi^*

来源：Journal of Statistical Planning and Inference, 2011, 141(3): 1297-1306.

DOI：10.1016/j.jspi.2010.09.030

• Discriminant analysis
• Asymptotic expansion
• Probabilities of misclassification
• Asymptotic approximation
• Monotone missing samples

This paper proposes two asymptotic expansions relating to discrimination based on two-step monotone missing samples. These asymptotic expansions have been obtained by Okamoto (1963) and McLachlan (1973) for complete data under multivariate normality. This paper extends the results up to the terms of the first order in the case of two-step monotone missing samples, respectively. Especially, these asymptotic expansions play important roles in obtaining the asymptotic approximations for the probabilities of misclassification in discriminant analysis. The simulation studies have been also conducted in order to evaluate the accuracy of the approximation derived in this paper.

• 出版日期2011-3