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Expectation-Maximization algorithm for bi-variate Normal Inverse Gaussian distribution 1.0

  Date Added: May 11, 2013  |  Visits: 199

Expectation-Maximization algorithm for bi-variate Normal Inverse Gaussian distribution

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EM estimation of parameters of bi variate NIG distribution.The test file:1. Simulate biNIG sample with use of randraw.m (http://www.mathworks.com/matlabcentral/fileexchange/7309)or invgrnd.m (http://www.mathworks.com/matlabcentral/fileexchange/10934) .2. Calls EMBIVNIG.m (values of starting parameters are chosen arbitrary).3. Calls binigpp.m for P-P plot to check the fit.References: "EM-estimation and modeling of heavy-tailed processes with the multivariate normal inverse Gaussian distribution", Oigard, Hanssen, Hansen and Godtliebsen, Signal Processing, vol. 85 (2005), p. 1655-1673"The Two-Dimensional Hyperbolic Distribution and Related Distributions, with an Application to Johannsen's Bean Data", P. Blaesild, Biometrika, vol. 68, No. 1 (Apr., 1981), pp. 251-263, (Theorem 1 (a) & (c), p. 253)Any comments welcome :)

Requirements: No special requirements
Platforms: Matlab
Keyword: Distributionquot Godtliebsen Hanssen Hyperbolic Oigard Processing Quotthe Signal Twodimensional
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License: Shareware Size: 10 KB
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EXPECTATION-MAXIMIZATION ALGORITHM FOR BI-VARIATE NORMAL INVERSE GAUSSIAN DISTRIBUTION RELATED
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