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Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:

陈望学 博士, 吉首大学数学与统计学院

Inviter:  
Title:
Modified Maximum Likelihood Estimator of Scale Parameter Using Moving Extremes Ranked Set Sampling
Time & Venue:
2018.10.15 10:00-11:00 N109
Abstract:
A modified maximum likelihood estimator (MMLE) of scale parameter is considered under moving extremes ranked set sampling (MERSS), and its properties are obtained. For some usual scale distributions, we obtain explicit form of the MMLE and prove the MMLE is an unbiased estimator under MERSS. The simulation results show that the MMLE using MERSS is always more efficient than the MLE using simple random sampling, when the same sample size is used. The simulation results also show that the loss of efficiency in using the MMLE instead of the MLE is very small for small sample.
 

 

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