Optimal Parameter Estimation of the Extreme Value Distribution Based on a Type II Censored Sample

2003 ◽  
Vol 32 (3) ◽  
pp. 533-554 ◽  
Author(s):  
Jong-Wuu Wu ◽  
Pai-Ling Li
Keyword(s):  
Parameter Estimation ◽  
Optimal Parameter ◽  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Type Ii ◽  
Optimal Parameter Estimation ◽  
Censored Sample ◽  
Type Ii Censored Sample

scholarly journals Weighted Moments Estimators of the Parameters for the Extreme Value Distribution Based on the Multiply Type II Censored Sample

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Jong-Wuu Wu ◽  
Sheau-Chiann Chen ◽  
Wen-Chuan Lee ◽  
Heng-Yi Lai
Keyword(s):  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Estimation Methods ◽  
Type Ii ◽  
Scale Parameters ◽  
Censored Sample ◽  
Best Linear Unbiased ◽  
Moments Estimators ◽  
Type Ii Censored Sample

We propose the weighted moments estimators (WMEs) of the location and scale parameters for the extreme value distribution based on the multiply type II censored sample. Simulated mean squared errors (MSEs) of best linear unbiased estimator (BLUE) and exact MSEs of WMEs are compared to study the behavior of different estimation methods. The results show the best estimator among the WMEs and BLUE under different combinations of censoring schemes.

Convergence rates for the ultimate and pentultimate approximations in extreme-value theory

1982 ◽  
Vol 14 (04) ◽  
pp. 833-854 ◽  
Author(s):  
Jonathan P. Cohen
Keyword(s):  
Extreme Value Theory ◽  
Convergence Rates ◽  
Domain Of Attraction ◽  
Extreme Value Distribution ◽  
Rates Of Convergence ◽  
Value Theory ◽  
Extreme Value ◽  
Value Distribution ◽  
Type I ◽  
Type Ii

Let F be a distribution in the domain of attraction of the type I extreme-value distribution Λ(x). In this paper we derive uniform rates of convergence of Fn to Λfor a large class of distributions F. We also generalise the penultimate approximation of Fisher and Tippett (1928) and show that for many F a type II or type III extreme-value distribution gives a better approximation than the limiting type I distribution.

Semi-Parametric Statistical Model for Extreme Value Statistical Models and Application in Automatic Control

2014 ◽  
Vol 680 ◽  
pp. 455-458
Author(s):  
Yu Han
Keyword(s):  
Parameter Estimation ◽  
Automatic Control ◽  
Statistical Models ◽  
Estimation Method ◽  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Vector Model ◽  
Extreme Statistics ◽  
The Impact

The frequency that extreme events appear in the life is low,but once it appears,the impact will be significant; many scholars have conducted in depth research and found that statistical theory of extreme value. The theory of extreme statistics plays a more and more important role in many fields such as automatic control, assembly line etc. This paper,makes an in-depth research towards the characteristics and parameter estimation of the extreme value statistical models,as well as the application,mainly analyzes the Bayes parameter estimation method of extreme value distribution,the extreme value distribution theory and Copula function random vector model.

Convergence rates for the ultimate and pentultimate approximations in extreme-value theory

1982 ◽  
Vol 14 (4) ◽  
pp. 833-854 ◽  
Author(s):  
Jonathan P. Cohen
Keyword(s):  
Extreme Value Theory ◽  
Convergence Rates ◽  
Domain Of Attraction ◽  
Extreme Value Distribution ◽  
Rates Of Convergence ◽  
Value Theory ◽  
Extreme Value ◽  
Value Distribution ◽  
Type I ◽  
Type Ii

Let F be a distribution in the domain of attraction of the type I extreme-value distribution Λ(x). In this paper we derive uniform rates of convergence of Fn to Λfor a large class of distributions F. We also generalise the penultimate approximation of Fisher and Tippett (1928) and show that for many F a type II or type III extreme-value distribution gives a better approximation than the limiting type I distribution.

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