missing information principle
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Parameter Estimation for Lomax Distribution under Type II Censoring

2014 ◽  
Vol 912-914 ◽  
pp. 1663-1668 ◽  
Author(s):  
Min Yang ◽  
Cheng Dong Wei ◽  
Qing Zhu Fan
Keyword(s):  
Parameter Estimation ◽  
Fisher Information Matrix ◽  
Numerical Study ◽  
Information Matrix ◽  
Maximum Likelihood Estimates ◽  
Type Ii ◽  
Missing Information ◽  
Type Ii Censoring ◽  
Lomax Distribution ◽  
Missing Information Principle

In this paper, The problem of estimating unknown paramaters of Lomax distribution is considered under the assumption that samples are type-II censoring. The maximum likelihood estimates are developed for unknown paramaters using EM algorithm and NR method. We obtain the observed Fisher information matrix using the missing information principle . A numerical study is performed to compare the proposed estimate.

Median regression and the missing information principle

2001 ◽  
Vol 13 (5) ◽  
pp. 709-727 ◽  
Author(s):  
Ian W. Mckeague ◽  
Sundarraman Subramanian ◽  
Yanqing sun
Keyword(s):  
Missing Information ◽  
Median Regression ◽  
Missing Information Principle
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