Alternative proposed bivariate negative binomial distribution.

Regression analysis is a statistical method that can explain the causal relationship between one response variable and one or more predictor variables. In general, the response variables are continuous data and normally distributed. However, in some applications, the response variable to be analyzed is in the form of discrete data, so the Poisson regression model is used, with the assumption that the mean and variance are the same or is called equal dispersion. However, in some real data, there is often over dispersion so the researchers model the count data with negative binomial regression. For cases with two (discrete) count variables that are correlated and require joint estimation, a bivariate count data regression model is used. One of them is the bivariate Poisson regression model which is widely used for correlated and equidistant bivariate data and for the case of over dispersion using a bivariate negative binomial model. In decreasing the combined distribution of the negative bivariate binomial distribution, several approaches can be used, in this paper we will show the results of the negative bivariate binomial distribution using the Cheon Method. With the alternative combined distribution of the negative bivariate binomial distribution, it can provide a more effective solution in solving problems in negative bivariate binomial regression. [ABSTRACT FROM AUTHOR]