土地利用动态的马尔可夫模型
A Markov model of land use dynamics
摘要：
应用马尔可夫链模拟农业演替是众所周知的。在大多数情况下，主要问题是模型的推断，即转移阵的估计。在这项工作中，我们提出的方法来估计的转移阵从历史的观察。除了最大似然估计（MLE），我们还考虑了与Jeffreys先验相关的贝叶斯估计。该贝叶斯估计量将通过马尔可夫链蒙特卡罗（MCMC）方法近似。我们还提出了一种基于逗留时间的方法来检验马尔可夫链模型对数据集的适用性。
英文摘要：
The application of the Markov chain to modeling agricultural succession is well known. In most cases, the main problem is the inference of the model, i.e. the estimation of the transition matrix. In this work we present methods to estimate the transition matrix from historical observations. In addition to the estimator of maximum likelihood (MLE), we also consider the Bayes estimator associated with the Jeffreys prior. This Bayes estimator will be approximated by a Markov chain Monte Carlo (MCMC) method. We also propose a method based on the sojourn time to test the adequation of Markov chain model to the dataset.
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