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Estimation for Mean and Standard Deviation of Normal Distribution under Type II Censoring
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 Title & Authors
Estimation for Mean and Standard Deviation of Normal Distribution under Type II Censoring
Kim, Namhyun;
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 Abstract
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 explicit form for the estimators using a method to approximate the likelihood function. The derived estimators are a special case of Balakrishnan et al. (2003). We compare the estimators with the Gupta's linear estimators through simulation. Gupta's linear estimators are unbiased and easily calculated; subsequently, the proposed estimators have better performance for mean squared errors and variances, although they show bigger biases especially when the ratio of the complete data is small.
 Keywords
Asymptotic variances;maximum likelihood estimators;normal distribution;plotting position;type II censoring;
 Language
English
 Cited by
 References
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