An EM type algorithm for maximum likelihood estimation of the normal-inverse Gaussian distribution

By Dimitris Karlis. 2002

134 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5e7b458931af53f27300575069dd6feebf459c26

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Kjersti Aas
2. Ingrid Hobæk Haff
3. Reiichiro Kawai
4. Hiroki Masuda
5. Claudia Czado
6. Eike C. Brechmann
7. V. Todorov
8. Ulf Schepsmeier

In Statistics and Probability

1. Kjersti Aas
2. Ingrid Hobæk Haff
3. Reiichiro Kawai
4. Hiroki Masuda
5. Claudia Czado
6. Eike C. Brechmann
7. Yasuhiro Omori
8. Toshinao Yoshiba

Citations in the corpus

• The Generalized Hyperbolic Skew Student’s t-Distribution (2006, methodology): “The moments of the GIG(λ, δ, γ) distribution are given by (Karlis, 2002) E(Zr) = ( δ γ )r Kλ+r(δ γ) Kλ(δ γ) .”
• Local asymptotic normality for normal inverse Gaussian Lévy processes with high-frequency sampling (2010, methodology): “Among others, for possible practical devices for computing estimates, we refer to EM type algorithm (Karlis [12]) and MCMC based Bayesian estimation (Karlis and Lillestöl [13]).”