
AbstractA new bivariate negative binomial distribution is derived by convoluting an existing bivariate geometric distribution; the probability function has six parameters and admits of positive or negative correlations and linear or nonlinear regressions. Given are the moments to order two and, for special cases, the regression function and a recursive formula for the probabilities. Purely numerical procedures are utilized in obtaining maximum likelihood estimates of the parameters. A data set with a nonlinear empirical regression function and another with negative sample correlation coefficient are discussed.
maximum likelihood estimates of the parameters, nonlinear empirical regression function, Linear regression; mixed models, bivariate negative binomial distribution, Characterization and structure theory of statistical distributions, Distribution theory
maximum likelihood estimates of the parameters, nonlinear empirical regression function, Linear regression; mixed models, bivariate negative binomial distribution, Characterization and structure theory of statistical distributions, Distribution theory
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