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A Sample Coverage Approach to Multiple-System Estimation with Application to Census Undercount

多系统估计的样本覆盖率方法及其在人口普查漏计中的应用

The concept of “sample coverage” used in animal abundance estimation is modified to evaluate the undercount of a census. Lack of independence between the census and its postenumeration survey leads to correlation bias for the standard estimator of population size. An additional recapture sample (besides the census and postenumeration survey) can be used to estimate the correlation bias due to two types of dependences. This work expresses the correlation bias for the…

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Estimating the Number of Classes via Sample Coverage

通过样本覆盖率估计类别总数

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…

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On Estimating the Probability of Discovering a New Species

发现新物种概率的估计

We search a population by selecting one member at a time with replacement and observing the species of each selected member. We are interested in predicting the conditional probability of discovering a new species in the next selection after $n$ observations. The existence and asymptotic behavior of the uniformly minimum variance unbiased estimator of the unconditional probability is investigated under the condition that the species are uniformly distributed. We also compare…

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Approximate Mean Squared Errors of Estimators of Reliability for k -out-of- m Systems in the Independent Exponential Case

独立指数寿命下 k-out-of-m 系统可靠性估计量的近似均方误差

Suppose S is a system with m independent components such that the system functions if and only if at least k components operate. Assume that the component lifetimes are identically exponentially distributed. This work provides simple approximation formulas for the mean squared errors of the minimum variance unbiased and the maximum likelihood estimators of reliability of this system. The performance of the proposed approximation formulas is investigated.

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