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Maximum likelihood estimation for the exponential power function parameters

 

作者: G. Agrò,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1995）
卷期: Volume 24, issue 2  

页码: 523-536

 

ISSN:0361-0918

 

年代: 1995

 

DOI:10.1080/03610919508813255

 

出版商: Marcel Dekker, Inc.

 

关键词: maximum likelihood estimation;profile likelihood function;exponential power function;information matrix;regularity conditions;parameter bias

 

数据来源: Taylor

 

摘要:

This paper addresses the problem of obtaining maximum likelihood estimates for the three parameters of the exponential power function; the information matrix is derived and the covariance matrix is here presented; the regularity conditions which ensure asymptotic normality and efficiency are examined. A numerical investigation is performed for exploring the bias and variance of the maximum likelihood estimates and their dependence on sample size and shape parameter.

 

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