# On generalized log-Moyal distribution: A new heavy tailed size distribution

*Deepesh Bhati* and
*Sreenivasan Ravi*

*Insurance: Mathematics and Economics*, 2018, vol. 79, issue C, 247-259

**Abstract:**
A new class of distributions, the generalized log-Moyal, suitable for modelling heavy tailed data is proposed in this article. This class exhibits desirable properties relevant to actuarial science and inference. The proposed distribution can be related to some well known distributions like Moyal, folded-normal and chi-square. Statistical inference of the model parameters is discussed using the method of quantiles and the method of maximum likelihood estimation. Three celebrated data sets, namely, Norwegian fire insurance losses, Danish fire insurance losses and vehicle insurance losses, are used to show the applicability of the new class of distributions. Parametric regression modelling is discussed assuming that the response variable follows the generalized log-Moyal distribution.

**Keywords:** Danish fire insurance losses; Heavy tailed distributions; Limited expected value; Log-Moyal distribution; Norwegian fire insurance losses; Regression modelling; Vehicle insurance losses (search for similar items in EconPapers)

**Date:** 2018

**References:** View references in EconPapers View complete reference list from CitEc

**Citations** Track citations by RSS feed

**Downloads:** (external link)

http://www.sciencedirect.com/science/article/pii/S0167668717302871

Full text for ScienceDirect subscribers only

**Related works:**

This item may be available elsewhere in EconPapers: Search for items with the same title.

**Export reference:** BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text

**Persistent link:** https://EconPapers.repec.org/RePEc:eee:insuma:v:79:y:2018:i:c:p:247-259

Access Statistics for this article

Insurance: Mathematics and Economics is currently edited by *R. Kaas*, *Hansjoerg Albrecher*, *M. J. Goovaerts* and *E. S. W. Shiu*

More articles in Insurance: Mathematics and Economics from Elsevier

Bibliographic data for series maintained by Dana Niculescu ().