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Title

On simulating multivariate non-normal distributions from the generalized lambda distribution
Authors

TC Headrick
A Mugdadi
Journal / Anthology

COMPUTATIONAL STATISTICS & DATA ANALYSIS
Year: 2006
Volume: 50
Issue: 11
Page range: 3343-3353
Description

The class of generalized lambda distributions (GLDs) is primarily used for modeling univariate real-world data. The GLD has not been as popular as some other methods for simulating observations from multivariate distributions because of computational difficulties. In view of this, the methodology and algorithms are presented for extending the GLD from univariate to multivariate data generation with an emphasis on reducing computational difficulties. Algorithms written in Mathematica 5.1 and Fortran 77 are provided for implementing the procedure and are available from the authors. A numerical example is provided and a Monte Carlo simulation was conducted to confirm and demonstrate the methodology.
Subjects

*Applied Mathematics > Numerical Methods
*Mathematics > Probability and Statistics
Keywords

correlated data, generalized lambda distribution, Monte Carlo simulation, multivariate non-normal data generation