A New Multivariate Markov Chain Model for Adding a New Categorical Data Sequence | Zendy

Chao Wang | Zendy; TingZhu Huang | Zendy; WaiKi Ching | Zendy

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A New Multivariate Markov Chain Model for Adding a New Categorical Data Sequence

Author(s) -

Chao Wang,

TingZhu Huang,

WaiKi Ching

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/502808

Subject(s) - multivariate statistics , markov chain , categorical variable , algorithm , computer science , artificial intelligence , machine learning

We propose a new multivariate Markov chain model for adding a new categorical data sequence. The number of the parameters in the new multivariate Markov chain model is only (3s) less than ((s+1)2) the number of the parameters in the former multivariate Markov chain model. Numerical experiments demonstrate the benefits of the new multivariate Markov chain model on saving computational resources

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