Simulation techniques for generalized Gaussian densities
Martina Nardon () and
No 145, Working Papers from Department of Applied Mathematics, Università Ca' Foscari Venezia
This contribution deals with Monte Carlo simulation of generalized Gaussian random variables. Such a parametric family of distributions has been proposed in many applications in science to describe physical phenomena and in engineering, and it seems also useful in modeling economic and financial data. For values of the shape parameter a within a certain range, the distribution presents heavy tails. In particular, the cases a=1/3 and a=1/2 are considered. For such values of the shape parameter, different simulation methods are assessed.
Keywords: Generalized Gaussian density; heavy tails; transformations of rendom variables; Monte Carlo simulation; Lambert W function (search for similar items in EconPapers)
JEL-codes: C15 C16 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:vnm:wpaper:145
Access Statistics for this paper
More papers in Working Papers from Department of Applied Mathematics, Università Ca' Foscari Venezia Contact information at EDIRC.
Bibliographic data for series maintained by Marco LiCalzi ().