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。关 键 词 巴斯卡分布; 极大似然估计; 置信区间; 强相合性; 超越方程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.Key words Pascal distribution; maximum likelihood estimate; confidence interval; strong consistency; transcendental equation
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