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Article
Simulating Controlled Variate and Rank Correlations Based on the Power Method Transformation
Communications in Statistics: Simulation and Computation (2008)
  • Todd C. Headrick, Southern Illinois University Carbondale
  • Simon Y. Aman
  • T. Mark Beasley
Abstract
The power method transformation is a popular algorithm used for simulating correlated non normal continuous variates because of its simplicity and ease of execution. Statistical models may consist of continuous and (or) ranked variates. In view of this, the methodology is derived for simulating controlled correlation structures between non normal (a) variates, (b) ranks, and (c) variates with ranks in the context of the power method. The correlation structure between variate-values and their associated rank-order is also derived for the power method. As such, a measure of the potential loss of information is provided when ranks are used in place of variate-values. The results of a Monte Carlo simulation are provided to confirm and demonstrate the methodology.
Keywords
  • Cumulants,
  • Monte Carlo,
  • Non-normal,
  • Rank-Order Statistics,
  • Simulation
Publication Date
2008
Citation Information
Todd C. Headrick, Simon Y. Aman and T. Mark Beasley. "Simulating Controlled Variate and Rank Correlations Based on the Power Method Transformation" Communications in Statistics: Simulation and Computation Vol. 37 Iss. 3 (2008)
Available at: http://works.bepress.com/todd_headrick/34/