Statistical properties of the generalized inverse Gaussian distribution
著者
書誌事項
Statistical properties of the generalized inverse Gaussian distribution
（Lecture notes in statistics, v. 9）
Springer-Verlag, c1982
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- : gw
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注記
Originally presented as the author's thesis (M.Sc.)--Aarhus University
Bibliography: p. 177-181
Includes index
内容説明・目次
内容説明
In 1978 the idea of studying the generalized inverse Gaussian distribution was proposed to me by Professor Ole Barndorff-Nielsen, who had come across the distribution in the study of the socalled hyperbolic distributions where it emerged in connection with the representation of the hyperbolic distributions as mixtures of normal distributions. The statistical properties of the generalized inverse Gaussian distribution were at that time virtually unde- veloped, but it turned out that the distribution has some nice properties, and models many sets of data satisfactorily. This work contains an account of the statistical properties of the distribu- tion as far as they are developed at present. The work was done at the Department of Theoretical Statistics, Aarhus University, mostly in 1979, and was partial fulfilment to- wards my M.Sc. degree. I wish to convey my warm thanks to Ole Barn- dorff-Nielsen and Preben BI~sild for their advice and for comments on earlier versions of the manuscript and to Jette Hamborg for her skilful typing.
目次
1 Introduction.- 2 Basic properties.- 2.1 Moments and cumulants.- 3 Related distributions.- 3.1 Normal approximations.- 3.2 Powers and logarithms of generalized inverse Gaussian variates.- 3.3 Products and quotients of generalized inverse Gaussian variates.- 3.4 A generalized inverse Gaussian Markov process.- 3.5 The generalized hyperbolic distribution.- 4 Maximum likelihood estimation.- 4.1 Estimation for fixed ?.- 4.2 On the asymptotic distribution of the maximum likelihood estimate for fixed ?.- 4.3 The partially maximized log-likelihood for ?, estimation of ?.- 4.4 Estimation of ? when ? and ? are fixed.- 4.5 Estimation of ? when ? and ?>0 are fixed.- 5 Inference.- 5.1 Distribution results.- 5.2 Inference about ?.- 5.3 Inference about ?.- 5.4 One-way analysis of variance.- 5.5 A regression model.- 6 The hazard function. Lifetime models..- 6.1 Description of the hazard function.- 7 Examples.- 7.1 Failures of airconditioning equipment.- 7.2 Pulses along a nerve fibre.- 7.3 Traffic data.- 7.4 Repair time data.- 7.5 Fracture toughness of MIG welds.- References.- List of symbols.
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