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Bivariate Poisson-Lindley Distribution with Application | Science Publications

机译:双变量泊松-林德利分布及其应用科学出版物

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> >This study applies a Bivariate Poisson-Lindley (BPL) distribution for modeling dependent and over-dispersed count data. The advantage of using this form of BPL distribution is that the correlation coefficient can be positive, zero or negative, depending on the multiplicative factor parameter. Several properties such as mean, variance and correlation coefficient of the BPL distribution are discussed. A numerical example is given and the BPL distribution is compared to Bivariate Poisson (BP) and Bivariate Negative Binomial (BNB) distributions which also allow the correlation coefficient to be positive, zero or negative. The results show that BPL distribution provides the smallest Akaike Information Criterion (AIC), indicating that the distribution can be used as an alternative for fitting dependent and over-dispersed count data, with either negative or positive correlation.
机译: > >该研究将双变量Poisson-Lindley(BPL)分布用于对依赖和过度分散的计数数据进行建模。使用这种形式的BPL分布的优势在于,取决于乘数因子参数,相关系数可以为正,零或负。讨论了一些特性,例如BPL分布的均值,方差和相关系数。给出了一个数值示例,并将BPL分布与双变量Poisson(BP)和双变量负二项式(BNB)分布进行了比较,这也使相关系数为正,零或负。结果表明,BPL分布提供了最小的Akaike信息准则(AIC),表明该分布可以用作拟合具有负相关或正相关的依赖和过度分散的计数数据的替代方法。

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