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Comparison of parameter estimation methods for normal inverse Gaussian distribution

Authors
Yoon, JeongyoenKim, JiyeonSong, Seongjoo
Issue Date
1월-2020
Publisher
KOREAN STATISTICAL SOC
Keywords
normal inverse Gaussian distribution; feasible domain; maximum likelihood estimation; method of moments estimation; adjusted estimation
Citation
COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, v.27, no.1, pp.97 - 108
Indexed
SCOPUS
KCI
Journal Title
COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS
Volume
27
Number
1
Start Page
97
End Page
108
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/58560
DOI
10.29220/CSAM.2020.27.1.097
ISSN
2287-7843
Abstract
This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.
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