EM-estimation and modeling of heavy-tailed processes with the multivariate normal inverse Gaussian distribution
- 1 August 2005
- journal article
- research article
- Published by Elsevier BV in Signal Processing
- Vol. 85 (8), 1655-1673
- https://doi.org/10.1016/j.sigpro.2005.03.005
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- Homomorphic wavelet-based statistical despeckling of SAR imagesIEEE Transactions on Geoscience and Remote Sensing, 2004
- The multivariate normal inverse Gaussian heavy-tailed distribution: simulation and estimationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Apparent scalingFinance and Stochastics, 2001
- The normal inverse Gaussian distribution as a model for MUIPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2001
- Normal Inverse Gaussian Distributions and Stochastic Volatility ModellingScandinavian Journal of Statistics, 1997
- Performance of optimum and suboptimum receivers in the presence of impulsive noise modeled as an alpha-stable processIEEE Transactions on Communications, 1995
- Maximum likelihood localization of sources in noise modeled as a stable processIEEE Transactions on Signal Processing, 1995
- Normal Variance-Mean Mixtures and z DistributionsInternational Statistical Review / Revue Internationale de Statistique, 1982
- Statistical Properties of Inverse Gaussian Distributions. IIThe Annals of Mathematical Statistics, 1957
- Statistical Properties of Inverse Gaussian Distributions. IThe Annals of Mathematical Statistics, 1957