ESTIMATING THE NUMBER OF CLASSES VIA SAMPLE COVERAGE
ESTIMATING THE NUMBER OF CLASSES VIA SAMPLE COVERAGE
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DOI：
10.2307/2290471
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发表时间：
1992-03-01
影响因子：
3.7
通讯作者：
LEE, SM
中科院分区：
文献类型：
--
作者：
CHAO, A;LEE, SM
假设从具有未知数量的类和可能不相等的类概率的总体中抽取随机样本。提出了一种非参数估计技术，利用样本覆盖的思想来估计类的数量，样本覆盖被定义为所观察的类的单元概率之和。由于预期的样本覆盖率可以很好地估计，我们有动机找到它的作用，估计类的数量。这项工作概括了Esty的结果，一个非参数的方法和扩展Darroch和拉特克利夫，将类概率的异质性。的类大小的变异系数被证明在推荐的估计程序中起着重要的作用。所提出的估计的性能进行了研究，通过蒙特卡罗模拟。
Assume that a random sample is drawn from a population with unknown number of classes and possibly unequal class probabilities. A nonparametric estimation technique is proposed to estimate the number of classes using the idea of sample coverage, which is defined as the sum of the cell probabilities of the observed classes. Since expected sample coverage can be well estimated, we were motivated to find its role in the estimation of the number of classes. This work generalizes the result of Esty to a nonparametric approach and extends Darroch and Ratcliff to incorporate the heterogeneity of the class probabilities. The coefficient of variation of the class sizes is shown to play an important role in the recommended estimation procedures. The performance of the proposed estimators is investigated by means of Monte Carlo simulations.