کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1148464 | 957835 | 2008 | 16 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Modeling statistical dependence of Markov chains via copula models Modeling statistical dependence of Markov chains via copula models](/preview/png/1148464.png)
Conditional probability distributions have been commonly used in modeling Markov chains. In this paper we consider an alternative approach based on copulas to investigate Markov-type dependence structures. Based on the realization of a single Markov chain, we estimate the parameters using one- and two-stage estimation procedures. We derive asymptotic properties of the marginal and copula parameter estimators and compare performance of the estimation procedures based on Monte Carlo simulations. At low and moderate dependence structures the two-stage estimation has comparable performance as the maximum likelihood estimation. In addition we propose a parametric pseudo-likelihood ratio test for copula model selection under the two-stage procedure. We apply the proposed methods to an environmental data set.
Journal: Journal of Statistical Planning and Inference - Volume 138, Issue 4, 1 April 2008, Pages 1131–1146