Graduation Year
2007
Document Type
Dissertation
Degree
Ph.D.
Degree Granting Department
Mathematics and Statistics
Major Professor
Arunava Mukherjea, Ph.D.
Committee Member
Kandethody Ramachandran, Ph.D.
Committee Member
Stephen Suen, Ph.D.
Committee Member
Yuncheng You, Ph.D.
Keywords
Tri-variate normal, Parameter identification, Minimum variate, Asymptotic order, Tail probabilities
Abstract
Let (X1, X2, X3) be a tri-variate normal vector with a non-singular co-variance matrix ∑ , where for i ≠ j, ∑ij < 0 . It is shown here that it is then possible to determine the three means, the three variances and the three correlation coefficients based only on the knowledge of the probability density function for the minimum variate Y = min{X1 , X2 , X3 }. We will present a method for identifying the nine parameters which consists of careful determination of the asymptotic orders of various bivariate tail probabilities.
Scholar Commons Citation
Davis, John C., "Identification of the Parameters When the Density of the Minimum is Given" (2007). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/691