A New Model for Multivariate Markov Chains

被引：14
|
作者：
Nicolau, Joao [1 ,2 ]
机构：
[1] ISEG ULisboa, Lisbon, Portugal
[2] CEMAPRE, Lisbon, Portugal
来源：
SCANDINAVIAN JOURNAL OF STATISTICS | 2014年 / 41卷 / 04期
关键词：
high-order Markov chains; maximum likelihood method; mixture transition distribution; multivariate Markov chains; TRANSITION DISTRIBUTION MODEL; TIME-SERIES;
D O I：
10.1111/sjos.12087
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We propose a new model for multivariate Markov chains of order one or higher on the basis of the mixture transition distribution (MTD) model. We call it the MTD-Probit. The proposed model presents two attractive features: it is completely free of constraints, thereby facilitating the estimation procedure, and it is more precise at estimating the transition probabilities of a multivariate or higher-order Markov chain than the standard MTD model.
引用
收藏
页码：1124 / 1135
页数：12
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