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On Simulating Univariate and Multivariate Burr Type III and Type XII Distributions
Applied Mathematical Sciences (2010)
  • Todd C. Headrick, Southern Illinois University Carbondale
  • Mohan D. Pant, University of Texas at Arlington
  • Yanyan Sheng, Southern Illinois University Carbondale
Abstract
This paper describes a method for simulating univariate and multivariate Burr Type III and Type XII distributions with specified correlation matrices. The methodology is based on the derivation of the parametric forms of a pdf and cdf for this family of distributions. The paper shows how shape parameters can be computed for specified values of skew and kurtosis. It is also demonstrated how to compute percentage points and other measures of central tendency such as the mode, median, and trimmed mean. Examples are provided to demonstrate how this Burr family can be used in the context of distribution fitting using real data sets. The results of a Monte Carlo simulation are provided to confirm that the proposed method generates distributions with user specified values of skew, kurtosis, and intercorrelation. Tabled values of shape parameters and boundary values of kurtosis are also provided in the appendices for the user.
Keywords
  • Distribution fitting,
  • Moments,
  • Monte Carlo,
  • Random variable generation,
  • Simulation
Publication Date
Spring March 5, 2010
Citation Information
Todd C. Headrick, Mohan D. Pant and Yanyan Sheng. "On Simulating Univariate and Multivariate Burr Type III and Type XII Distributions" Applied Mathematical Sciences Vol. 4 Iss. 45 (2010)
Available at: http://works.bepress.com/mohan_pant/11/