Inference for Likelihood Ratio Ordering in the Two-Sample Problem
Inference for Likelihood Ratio Ordering in the Two-Sample Problem
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DOI：
10.1080/01621459.1995.10476605
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发表时间：
1995-09
影响因子：
3.7
通讯作者：
R. Dykstra;S. Kochar;Tim Robertson
中科院分区：
文献类型：
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作者：
R. Dykstra;S. Kochar;Tim Robertson
摘要在似然比有序约束下，得到了两个多项式概率向量的极大似然估计。我们将这种估计方法推广到两个单变量分布的情况，并证明了估计量的强相合性。我们还推导并研究了似然比统计量的渐近分布，用于检验两个离散概率分布的相等性，以证明其中一个分布在似然比排序意义上大于另一个分布。最后，我们检查了来自波士顿合作药物监测计划的关于平均每日胰岛素剂量的数据集，并将我们的测试程序与其他随机顺序的测试程序进行了比较。
Abstract We obtain the maximum likelihood estimators of two multinomial probability vectors under the constraint that they are likelihood ratio ordered. We extend this estimation approach to the case of two univariate distributions and show strong consistency of the estimators. We also derive and study the asymptotic distribution of the likelihood ratio statistic for testing the equality of two discrete probability distributions against the alternative that one distribution is greater than the other in the likelihood ratio ordering sense. Finally, we examine a data set pertaining to average daily insulin dose from the Boston Collaborative Drug Surveillance Program and compare our testing procedure to testing procedures for other stochastic orderings.