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Further properties of random orthogonal matrix simulation
journal contribution
posted on 2023-06-08, 12:23 authored by Daniel Ledermann, Carol AlexanderCarol AlexanderRandom orthogonal matrix (ROM) simulation is a very fast procedure for generating multivariate random samples that always have exactly the same mean, covariance and Mardia multivariate skewness and kurtosis. This paper investigates how the properties of parametric, data-specific and deterministic ROM simulations are influenced by the choice of orthogonal matrix. Specifically, we consider how cyclic and general permutation matrices alter their time-series properties, and how three classes of rotation matrices – upper Hessenberg, Cayley, and exponential – influence both the unconditional moments of the marginal distributions and the behaviour of skewness when samples are concatenated. We also perform an experiment which demonstrates that parametric ROM simulation can be hundreds of times faster than equivalent Monte Carlo simulation.
History
Publication status
- Published
Journal
Mathematics and Computers in SimulationISSN
0378-4754Publisher
ElsevierExternal DOI
Volume
83Page range
56-79Department affiliated with
- Business and Management Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-09-11Usage metrics
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