Semiparametric estimation in the normal variance-mean mixture model. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Belomestny, Denis; Panov, Vladimir
• Is Part Of: Statistics. Volume 52:Issue 3(2018)
• Page Start: 571
• Page End: 589
• Publication Date: 2018-05-04
• Subjects: Variance-mean mixture model -- semiparametric inference -- Mellin transform -- generalized hyperbolic distribution -- deconvolution on groups; Mathematical statistics -- Periodicals; 519.505
• DOI: 10.1080/02331888.2018.1425865
• Languages: English
• ISSNs: 0233-1888

Abstract

ABSTRACT: In this paper we study the problem of statistical inference on the parameters of the semiparametric variance-mean mixtures. This class of mixtures has recently become rather popular in statistical and financial modelling. We design a semiparametric estimation procedure that first estimates the mean of the underlying normal distribution and then recovers non-parametrically the density of the corresponding mixing distribution. We illustrate the performance of our procedure on simulated and real data.