南方科技大学知识苑(SUSTech KC): Information geometry approach to parameter estimation in hidden Markov model

题名	Information geometry approach to parameter estimation in hidden Markov model
作者	Hayashi, Masahito1,2,3,4,5,6,7
通讯作者	Hayashi, Masahito
发表日期	2022-02-01
DOI	10.3150/21-BEJ1344
发表期刊	BERNOULLI 影响因子和分区
ISSN	1350-7265
EISSN	1573-9759
卷号	28 期号:1
摘要	We consider the estimation of the transition matrix of a hidden Markovian process by using information geometry with respect to transition matrices. In this paper, only the histogram of k-memory data is used for the estimation. To establish our method, we focus on a partial observation model with the Markovian process and we propose an efficient estimator whose asymptotic estimation error is given as the inverse of projective Fisher information of transition matrices. This estimator is applied to the estimation of the transition matrix of the hidden Markovian process. In this application, we carefully discuss the equivalence problem for hidden Markovian process on the tangent space.
关键词	Hidden Markov em-algorithm projective Fisher information matrix partial observation model
相关链接	[来源记录]
收录类别	SCI
语种	英语
学校署名	第一 ; 通讯
资助项目	Guangdong Provincial Key Laboratory[2019B121203002] ; JSPS["16KT0017","17H01280"]
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000718645900012
出版者	INT STATISTICAL INST
ESI学科分类	MATHEMATICS
来源库	Web of Science
引用统计	被引频次[WOS]：2
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/256838
专题	量子科学与工程研究院
作者单位	1.Southern Univ Sci & Technol, Shenzhen Inst Quantum Sci & Engn, Shenzhen, Peoples R China 2.Southern Univ Sci & Technol, Guangdong Prov Key Lab Quantum Sci & Engn, Shenzhen 518055, Peoples R China 3.Southern Univ Sci & Technol, Shenzhen Key Lab Quantum Sci & Engn, Shenzhen 518055, Peoples R China 4.Nagoya Univ, Grad Sch Math, Nagoya, Aichi 4648602, Japan 5.RIKEN, Ctr Adv Intelligence Project, Tokyo 1030027, Japan 6.Natl Univ Singapore, Ctr Quantum Technol, Singapore 117543, Singapore 7.Ctr Quantum Comp, Peng Cheng Lab, Shenzhen 518066, Peoples R China
第一作者单位	量子科学与工程研究院; 南方科技大学
通讯作者单位	量子科学与工程研究院; 南方科技大学
第一作者的第一单位	量子科学与工程研究院
推荐引用方式 GB/T 7714	Hayashi, Masahito. Information geometry approach to parameter estimation in hidden Markov model[J]. BERNOULLI,2022,28(1).
APA	Hayashi, Masahito.(2022).Information geometry approach to parameter estimation in hidden Markov model.BERNOULLI,28(1).
MLA	Hayashi, Masahito."Information geometry approach to parameter estimation in hidden Markov model".BERNOULLI 28.1(2022).