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Hidden Markov Models for multivariate functional data
Statistics & Probability Letters ( IF 0.8 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.spl.2020.108917
Andrea Martino , Giuseppina Guatteri , Anna Maria Paganoni

Abstract In this paper we extend the usual Hidden Markov Models framework, where the observed objects are univariate or multivariate data, to the case of functional data, by modeling the temporal structure of a system of multivariate curves evolving in time.

中文翻译:

多元函数数据的隐马尔可夫模型

摘要 在本文中,我们通过对随时间演化的多元曲线系统的时间结构进行建模,将通常的隐马尔可夫模型框架(其中观察对象是单变量或多元数据)扩展到函数数据的情况。
更新日期:2020-12-01
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