Economics at your fingertips  

Uni- and multivariate extensions of the sinh-arcsinh normal distribution applied to distributional regression

Yuanhua Feng () and Wolfgang Härdle ()

No 142, Working Papers CIE from Paderborn University, CIE Center for International Economics

Abstract: This paper introduces first an extended SAN (sinh-arcsinh normal) family of distri- butions by allowing the transformed normal random variable to be unstandardized. A Log-SAN transformation for non-negative random variables and the associate Log-SAN family of distributions are then proposed. Properties of those distribu- tions are investigated. A maximum likelihood estimation procedure is proposed. A chain mixed multivariate extension of the SAN distributions and a corresponding distributional regression model are then defined. Those approaches can help us to discover possible spurious or hidden bimodal property of a multivariate distribution. The proposals are illustrated by different examples.

Keywords: Extended SAS distribution; Log-SAS distribution; MLE; chain mixed multivariate distribution; distributional regression; spurious and hidden bimodality (search for similar items in EconPapers)
JEL-codes: C14 C51 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2021-05
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf)

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:

Access Statistics for this paper

More papers in Working Papers CIE from Paderborn University, CIE Center for International Economics Contact information at EDIRC.
Bibliographic data for series maintained by WP-WiWi-Info () and ().

Page updated 2023-11-11
Handle: RePEc:pdn:ciepap:142