Parameter estimation of Tukey-type distributions: A comparative analysis

Möstel, Linda; Fischer, Matthias; Pfälzner, Fabian; Pfeuffer, Marius

doi:10.1080/03610918.2019.1571604

Cited by 3 publications

(2 citation statements)

References 36 publications

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“…Likewise, the CF, probability density function, and cumulative distribution function can only be computed numerically. Several different techniques have been proposed for the estimation and fitting of the univariate Tukey g-and-h distribution (see the review paper by Möstel et al [39]). However, for the multivariate case, only a few methods are available.…”

Section: Multivariate Tukey G-and-h Distributionmentioning

confidence: 99%

Goodness-of-fit tests for multivariate skewed distributions based on the characteristic function

Karling¹,

Genton²,

Meintanis³

2023

Preprint

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We employ a general Monte Carlo method to test composite hypotheses of goodness-of-fit for several popular multivariate models that can accommodate both asymmetry and heavy tails. Specifically, we consider weighted L2-type tests based on a discrepancy measure involving the distance between empirical characteristic functions and thus avoid the need for employing corresponding population quantities which may be unknown or complicated to work with. The only requirements of our tests are that we should be able to draw samples from the distribution under test and possess a reasonable method of estimation of the unknown distributional parameters. Monte Carlo studies are conducted to investigate the performance of the test criteria in finite samples for several families of skewed distributions. Real-data examples are also included to illustrate our method.

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Section: Multivariate Tukey G-and-h Distributionmentioning

confidence: 99%

Goodness-of-fit tests for multivariate skewed distributions based on the characteristic function

Karling¹,

Genton²,

Meintanis³

2023

Preprint

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“…Linda Mostel et.al. (2019) estimated the parameters of the tukey-type distribution using Non-Bayeian methods as comparative analysis [6]. The paper is organized as follows: Section 2 reviews the Tukey gh distribution and its properties.…”

Section: Introductionmentioning

confidence: 99%

Bayesian estimation for the Tukey GH distribution with an application

Al-Saadony¹,

Mohammed²,

Melik³

2022

PEN

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Tukey GH is a transformed normal distribution, having two parameters (g,h). The g parameter represents skew measuring, and the h represents kurtosis measuring. Our motivation is to affect these parameters on the behavior for a simulation data and real data, such as the Iraqi stock market Index (ISX60) and the Standard and Poor's (SP500) index using the Bayesian framework. Then, our aim is to find the estimation for the parameters in this distribution using empirical and parametric Bayesian methods, and study the effective on the simulation and real data. The simulation study will be shown the behavior of the parameters with a different number of sampling and prior distributions. We will use the real data from ISX60 and SP500 index.

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