灵活的行为捕获-再捕获模型
Flexible behavioral capture-recapture modelling
摘要：
我们开发了一些新的策略，用于构建和拟合新的灵活类的参数捕获-再捕获模型，用于封闭种群，可用于更好地理解行为模式。我们首先依赖于一个条件概率参数化和审查如何把一个大的标准捕获-再捕获模型的子集作为一个合适的分区在等价类的全套条件概率参数。然后，我们建议使用新的合适的量化的条件二进制部分捕获历史作为一种设备，用于扩大灵活的行为模型的范围，也探索所有可能的分区的范围。我们展示了如何可以很容易地找到这样的模型在一个广义线性模型框架内的无条件极大似然估计。我们说明了我们的方法与一些已知的数据集和模拟研究的分析的潜力。
英文摘要：
We develop some new strategies for building and fitting new flexible classes of parametric capture-recapture models for closed populations which can be used to address a better understanding of behavioural patterns. We first rely on a conditional probability parameterization and review how to regard a large subset of standard capture-recapture models as a suitable partitioning in equivalence classes of the full set of conditional probability parameters. We then propose the use of new suitable quantifications of the conditioning binary partial capture histories as a device for enlarging the scope of flexible behavioural models and also exploring the range of all possible partitions. We show how one can easily find unconditional MLE of such models within a generalized linear model framework. We illustrate the potential of our approach with the analysis of some known datasets and a simulation study.
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