MAXIMUM LIKELIHOOD ESTIMATION OF THE FLEXIBLE WEIBULL DISTRIBUTION PARAMETERS BASED ON TYPE I CENSORED DATA

2012 ◽  
Vol 9 (1) ◽  
pp. 1-49
Author(s):  
Ahmed Hussen
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Weibull Distribution ◽  
Censored Data ◽  
Likelihood Estimation ◽  
Type I ◽  
Distribution Parameters

scholarly journals "Evaluation of Some Methods for Estimating the Weibull Distribution Parameters"

2017 ◽  
Vol 4 (2) ◽  
pp. 8-14
Author(s):  
J. A. Labban ◽  
H. H. Depheal
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Weibull Distribution ◽  
Least Squares ◽  
Mean Square Error ◽  
Random Sample ◽  
Likelihood Estimation ◽  
Mean Square ◽  
Distribution Parameters

"This paper some of different methods to estimate the parameters of the 2-Paramaters Weibull distribution such as (Maximum likelihood Estimation, Moments, Least Squares, Term Omission). Mean square error will be considered to compare methods fits in case to select the best one. There by simulation will be implemented to generate different random sample of the 2-parameters Weibull distribution, those contain (n=10, 50, 100, 200) iteration each 1000 times."

Random Censored Data MLE of Weibull Distribution Based on Simulink

2012 ◽  
Vol 542-543 ◽  
pp. 1463-1466
Author(s):  
Jing Zhao Shi ◽  
Rui Na Shao ◽  
Xiang Fu Li
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Weibull Distribution ◽  
Censored Data ◽  
Computer Programming ◽  
Likelihood Estimation ◽  
Random Censoring ◽  
Life Data ◽  
Transcendental Equations

Maximum likelihood estimation (MLE) is a commonly used method of Weibull distribution, but it needs to calculate the transcendental equations which is based on the computer programming. In this paper, we established a new MLE model of Weibull distribution in a case of random censoring. And this model was proved feasible and correct via three examples. At the same time, the model can be used for a variety of censored data and complete life data of Weibull distribution of MLE.

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