A Higher-order interactive hidden Markov model and its applications

被引：2

作者：

Zhu, Dong-Mei ^{[1
]}

Ching, Wai-Ki ^{[2
]}

Elliott, Robert J. ^{[3
]}

Siu, Tak-Kuen ^{[4
]}

Zhang, Lianmin ^{[5
]}

机构：

[1] Southeast Univ, Sch Econ & Management, Nanjing, Jiangsu, Peoples R China

[2] Univ Hong Kong, Dept Math, Adv Modeling & Appl Comp Lab, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China

[3] Univ Adelaide, Sch Math Sci, Adelaide, SA 5005, Australia

[4] Macquarie Univ, Fac Business & Econ, Dept Appl Finance & Actuarial Studies, Sydney, NSW 2109, Australia

[5] Nanjing Univ, Sch Management & Engn, Nanjing 210093, Jiangsu, Peoples R China

来源：

OR SPECTRUM | 2017年 / 39卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Interactive hidden Markov model; Hidden Markov model; Feedback effect; Stochastic difference equations; NONNEGATIVE MATRIX FACTORIZATION; QUEUING-NETWORKS; RISK;

D O I：

10.1007/s00291-017-0484-0

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

In this paper, we propose a higher-order interactive hidden Markov model, which incorporates both the feedback effects of observable states on hidden states and their mutual long-term dependence. The key idea of this model is to assume the probability laws governing both the observable and hidden states can be written as a pair of higher-order stochastic difference equations. We also present an efficient procedure, a heuristic algorithm, to estimate the hidden states of the chain and the model parameters. Real applications in SSE Composite Index data and default data are given to demonstrate the effectiveness of our proposed model and corresponding estimation method.

引用

页码：1055 / 1069

页数：15

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