Using D-Vine Copula for Modeling of Dependency of Categorical Data
Keywords:
Association, categorical variables, morning show, brands endorsement, tree diagramAbstract
This research introduces a new approach to D-Vine copula in the measuring of association between categorical variables. This paper used the D-Vine method of defining the tree diagram of the categorical data to find the dependence of the variable. D-Vine copula shows that the association between variables is strong under the simple and conditional probabilities and distribution. It is used to generate tree diagrams using nodes and edges of probabilities and conditional probability, which illustrate probability distributions and association between the variables. The purpose of the present study is (1) to find a linkage between morning show viewers having impact of brand endorsement (2) to empirically test the impact theory by examining the effect of the morning shows and brands image. Data is collected using an online survey, of the viewers of morning shows, the sample of 1750 observation is used to test the factors. Results of the D-Vine copula shows that the morning shows have a positive and strong impact on the brand image and purchase of the fashion products. As predicted, brand endorsement is positively associated with morning shows and celebrity images.
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