1
Master of Science in Statistics, Shahid Chamran University of Ahvaz, Iran
2
Department of Statistics, Shahid Chamran University, Ahvaz, Iran
Abstract
Joint functions can model the structure of the dependencies between variables. The appropriate joint function for a specific application is the function that best represents the dependencies between the data. From a theoretical perspective, goodness-of-fit tests are the best method for selecting joint functions. Several goodness-of-fit testing methods have been proposed for joint functions. In this article, in order to select appropriate goodness-of-fit testing methods, we will examine and numerically compare three different goodness-of-fit testing methods for joint functions, and examine their strengths and weaknesses relative to each other. Finally, we will analyze the proposed testing methods using Tehran Stock Exchange index data.
