An estimating function approach to the inference of catch-effort models
An estimating function approach to the inference of catch-effort models
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DOI：
10.1023/a:1009687514770
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发表时间：
1999-09-01
影响因子：
3.8
通讯作者：
Chang, SH
中科院分区：
文献类型：
--
作者：
Chao, A;Chang, SH
提出了一类考虑异质迁移概率的封闭种群捕获努力量模型。该模型包括三种类型的去除概率：乘法，泊松和逻辑。通常的移除和广义移除模型则成为特例。讨论了该模型与一类特殊的捕获-再捕获模型的等价性。采用统一的估计函数方法估计初始种群规模。对于齐次模型，基于最优估计函数的总体大小估计渐近等价于极大似然估计。我们的方法的一个优点是，它可以扩展到处理异质人口中的最大似然估计不存在。应用Bootstrap方法构造方差估计量和置信区间。我们用两个真实的数据例子来说明该方法。研究所提出的估计过程的性能的模拟研究结果。
A class of catch-effort models, which allows for heterogeneous removal probabilities, is proposed for closed populations. The model includes three types of removal probabilities: multiplicative, Poisson and logistic. The usual removal and generalized removal models then become special cases. The equivalence of the proposed model and a special type of capture-recapture model is discussed. A unified estimating function approach is used to estimate the initial population size. For the homogeneous model, the resulting population size estimator based on optimal estimating functions is asymptotically equivalent to the maximum likelihood estimator. One advantage for our approach is that it can be extended to handle the heterogeneous populations in which the maximum likelihood estimators do not exist. The bootstrap method is applied to construct variance estimators and confidence intervals. We illustrate the method by two real data examples. Results of a simulation study investigating the performance of the proposed estimation procedure are presented.