Pradel Roger
CEFE, UMR 5175, 1919 Route de Mende, F-34293 Montpellier, Cedex 05, France.
Biometrics. 2005 Jun;61(2):442-7. doi: 10.1111/j.1541-0420.2005.00318.x.
Capture-recapture models were originally developed to account for encounter probabilities that are less than 1 in free-ranging animal populations. Nowadays, these models can deal with the movement of animals between different locations and are also used to study transitions between different states. However, their use to estimate transitions between states does not account for uncertainty in state assignment. I present the extension of multievent models, which does incorporate this uncertainty. Multievent models belong to the family of hidden Markov models. I also show in this article that the memory model, in which the next state or location is influenced by the previous state occupied, can be fully treated within the framework of multievent models.
捕获-再捕获模型最初是为了应对自由放养动物种群中小于1的相遇概率而开发的。如今,这些模型可以处理动物在不同地点之间的移动,也被用于研究不同状态之间的转变。然而,它们用于估计状态之间的转变时并未考虑状态分配中的不确定性。我提出了多事件模型的扩展,该扩展确实纳入了这种不确定性。多事件模型属于隐马尔可夫模型家族。我还在本文中表明,其中下一状态或位置受先前占据状态影响的记忆模型,可以在多事件模型的框架内得到充分处理。