论文标题
用方向持久性和吸引人的点对动物运动进行建模
Modeling animal movement with directional persistence and attractive points
论文作者
论文摘要
研究人员目前很容易访问GPS技术，并且许多动物运动数据集可用。描述动物路径的模型的两个主要特征是定向持久性和吸引到空间点的吸引力。在这项工作中，我们提出了一种可以具有两个特征的新方法。我们的建议是一个隐藏的马尔可夫模型，具有新的排放分布。排放分布对上述两个特征进行建模，而隐藏的马尔可夫模型的潜在状态则是为了说明行为模式。我们证明该模型在贝叶斯框架中很容易实现。我们估计了代表澳大利亚记录的Maremma牧羊犬的GPS位置的激励数据的建议。获得的结果很容易解释，我们表明我们的建议优于主要竞争模型。
GPS technology is currently easily accessible to researchers, and many animal movement datasets are available. Two of the main features that a model which describes an animal's path can possess are directional persistence and attraction to a point in space. In this work, we propose a new approach that can have both characteristics. Our proposal is a hidden Markov model with a new emission distribution. The emission distribution models the two aforementioned characteristics, while the latent state of the hidden Markov model is needed to account for the behavioral modes. We show that the model is easy to implement in a Bayesian framework. We estimate our proposal on the motivating data that represent GPS locations of a Maremma Sheepdog recorded in Australia. The obtained results are easily interpretable and we show that our proposal outperforms the main competitive model.
