TITLE:
A Finite Mixture of Generalised Inverse Gaussian with Indexes -1/2 and -3/2 as Mixing Distribution for Normal Variance Mean Mixture with Application
AUTHORS:
Calvin B. Maina, Patrick G. O. Weke, Carolyne A. Ogutu, Joseph A. M. Ottieno
KEYWORDS:
Finite Mixture, Weighted Distribution, Mixed Model, EM-Algorithm
JOURNAL NAME:
Open Journal of Statistics,
Vol.11 No.6,
December
10,
2021
ABSTRACT: Mixture models have become more popular in modelling
compared to standard distributions. The mixing distributions play a role in
capturing the variability of the random variable in the conditional
distribution. Studies have lately focused on finite mixture models as mixing
distributions in the mixing mechanism. In the present work, we consider a
Normal Variance Mean mixture model. The
mixing distribution is a finite mixture of two special cases of Generalised Inverse Gaussian distribution with indexes -1/2 and -3/2. The parameters of the mixed
model are obtained via the Expectation-Maximization (EM) algorithm. The
iterative scheme is based on a presentation of the normal equations. An
application to some financial data has been done.