Negative binomial-reciprocal inverse Gaussian distribution: Statistical properties with applications
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In this article, we propose a new three parameter distribution by compounding negative binomial with reciprocal inverse Gaussian model called negative binomial-reciprocal inverse Gaussian distribution. This model is tractable with some important properties not only in actuarial science but in other fields as well where overdispersion pattern is seen. Some basic properties including recurrence relation of probabilities for computation of successive probabilities have been discussed. In its compound version, when the claims are absolutely continuous, an integral equation for the probability density function is discussed. Brief discussion about extension of univariate version have also been done to its respective multivariate version. parameters involved in the model have been estimated by Maximum Likelihood Estimation technique. Applications of the proposed distribution are carried out by taking two real count data sets. The result shown that the negative binomial-reciprocal inverse Gaussian distribution gives better fit when compared to the Poisson and negative binomial distributions.
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