Estimation for Mean and Standard Deviation of Normal Distribution under Type II Censoring

초록

In this paper, we consider maximum likelihood estimators of normal distribution based on type II censoring. Gupta (1952) and Cohen (1959, 1961) required a table for an auxiliary function to compute since they did not have an explicit form; however, we derive an explicitform for the estimators using a method to approximate the likelihood function. The derived estimators area special case of Balakrishnan et al. (2003). We compare the estimatorswith the Gupta's linear estimators through simulation. Gupta's linear estimators are unbiased andeasily calculated; subsequently, the proposed estimators have better performancefor mean squared errors and variances, although they show biggerbiases especially when the ratio of the complete data is small.

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