Parameter estimation of Tukey-type distributions: A comparative analysis

Möstel L, Fischer M, Pfaelzner F, Pfeuffer M (2019)

Publication Type: Journal article

Publication year: 2019

Journal

Communications in Statistics-Simulation and Computation Taylor & Francis: STM, Behavioural Science and Public Health Titles / Taylor & Francis

DOI: 10.1080/03610918.2019.1571604

Abstract

Tukey-type distributions (a generalization of Tukey's gh(normal)-distribution) are attractive for a broad spectrum of applications since they can explicitly model flexible skewness and kurtosis features of practical data. However, since the likelihood function is not available in closed-form, the derivation of an accurate estimation method plays a crucial role and henceforth various procedures to overcome this issue were introduced, especially for Tukey's gh(normal)-distribution. After extending these approaches to all Tukey-type distributions, our main contribution is to provide a comprehensive simulation study to compare the methods against each other. Moreover, we illustrate the practical usage for the Nikkei225 stock index data.

Authors with CRIS profile

Linda Möstel Lehrstuhl für Statistik und Ökonometrie Matthias Fischer Fachbereich Wirtschaftswissenschaften Marius Pfeuffer Lehrstuhl für Statistik und Ökonometrie

Related research project(s)

Kreditrating Jan. 1, 2017 - Jan. 1, 2020

Involved external institutions

Bayerische Landesbank DE Germany (DE)

How to cite

APA:

Möstel, L., Fischer, M., Pfaelzner, F., & Pfeuffer, M. (2019). Parameter estimation of Tukey-type distributions: A comparative analysis. Communications in Statistics-Simulation and Computation. https://doi.org/10.1080/03610918.2019.1571604

MLA:

Möstel, Linda, et al. "Parameter estimation of Tukey-type distributions: A comparative analysis." Communications in Statistics-Simulation and Computation (2019).

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