Document Type
Thesis
Degree
Master of Science (MS)
Major/Program
Statistics
First Advisor's Name
Jie Mi
First Advisor's Committee Title
Co-Committee Chair
Second Advisor's Name
Kai Huang
Second Advisor's Committee Title
Co-Committee Chair
Third Advisor's Name
Florence George
Keywords
Bivariate Normal Distribution, Trivariate Normal Distribution, Equal Variances and equal Covariances, Correlation Coefficient
Date of Defense
11-1-2013
Abstract
Suppose two or more variables are jointly normally distributed. If there is a common relationship between these variables it would be very important to quantify this relationship by a parameter called the correlation coefficient which measures its strength, and the use of it can develop an equation for predicting, and ultimately draw testable conclusion about the parent population.
This research focused on the correlation coefficient ρ for the bivariate and trivariate normal distribution when equal variances and equal covariances are considered. Particularly, we derived the maximum Likelihood Estimators (MLE) of the distribution parameters assuming all of them are unknown, and we studied the properties and asymptotic distribution of . Showing this asymptotic normality, we were able to construct confidence intervals of the correlation coefficient ρ and test hypothesis about ρ. With a series of simulations, the performance of our new estimators were studied and were compared with those estimators that already exist in the literature. The results indicated that the MLE has a better or similar performance than the others.
Identifier
FI13120413
Recommended Citation
Orjuela, Maria del Pilar, "A Study on the Correlation of Bivariate And Trivariate Normal Models" (2013). FIU Electronic Theses and Dissertations. 976.
https://digitalcommons.fiu.edu/etd/976
Tex Files
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