巴斯卡分布中未知参数的估计

Estimation of Unknown Parameter of Pascal Distribution

  • 摘要: 在巴斯卡分布的参数r,p都未知的情况下,讨论了未知参数的极大似然估计。结果表明,r的极大似然估计可转化成一个超越方程的求解,采用该超越方程的解作为r的估计量有强相合性,导出了在大样本下r和p的置信区间。并用实例验证了估计方法的合理性。

     

    Abstract: Maximum likelihood estimate is discussed in case both parameter r and p of Pascal distribution are unknown.. The result shows that maximum likelihood estimate of r can transfer to a solution of the transcendental equation. There is strong consistency to use the solution from estimation of r. The confidence interval of r and p in the big sample is introduced. The rationality of estimated method is proved from the real sample.

     

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