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Estimation of the Mean and Variance for Normal Distributions whose Both Sides are Truncated
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 Title & Authors
Estimation of the Mean and Variance for Normal Distributions whose Both Sides are Truncated
Hong, Chong-Sun; Choi, Yun-Young;
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 Abstract
In order to estimate the mean and variance for a Normal distribution which is truncated at both right and left sides, maximum likelihood estimators based on the entire sample from the original distribution are compared with the sample mean and variance of the censored sample which is the data remaining after truncation using simulation. We found that, surprisingly, the mean squared error of the mean based on the censored data Is smaller than that of the full sample estimators.
 Keywords
Bias;Censored-sample estimators;Full-sample estimators;MSE;
 Language
English
 Cited by
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