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Information matrix for a mixture of two inverse gaussian distributions

 

作者: E. K. AL-Hussaini,   K. E. Ahmad,  

 

期刊: Communications in Statistics - Simulation and Computation  (Taylor Available online 1984)
卷期: Volume 13, issue 6  

页码: 785-800

 

ISSN:0361-0918

 

年代: 1984

 

DOI:10.1080/03610918408812415

 

出版商: Marcel Dekker, Inc.

 

关键词: identifiability of finite mixtures;power series expansion

 

数据来源: Taylor

 

摘要:

In this paper, Fisher information matrix about the five parameters ρ, μ:1, μ2, λ1and λ2of a mixture of two Inverse Gaussian density functions is obtained. The Leguerre-Gauss quadrature formula is used to evaluate the essential integral on which the twenty five elements of the information matrix are based. Results involving the computation of the information about p are compared with those involving both the power series expansion and Simpson's method of integration. Laguerre-Gauss quadra-ture was found to lead to good approximations as compared with other methods. It was therefore chosen for the computations of the elements of the information matrix.

 

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