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Hidden Semi-Markov Models (HSMMs) have been extensively used for diverse applications where the objective is to analyze time series whose dynamics can be explained by a hidden process. A Comprehensive Guide to HSMM offers an accessible introduction to the framework of HSMM, covering the main methods and theoretical results for maximum likelihood estimation in HSMM. It also includes a unique review of existing R and Python software for HSMM estimation. The book then introduces less classical related topics, such as multi-chain HSMM and controlled HSMM, with an emphasis on the challenges related to computational complexity. This book is primarily intended for master’s and PhD students, researchers and academic faculty in the fields of statistics, applied probability, graphical models, Computer Science and connected domains. It is also meant to be accessible to practitioners involved in modeling, analysis or control of time series in the fields of reliability, theoretical ecology, signal processing, finance, medicine and epidemiology.
Overview – A Comprehensive Guide to HSMM: Theory, Software, and Advanced Extensions (ISTE Invoiced) by Nathalie Peyrard
Before you start the download of A Comprehensive Guide to HSMM: Theory, Software, and Advanced Extensions (ISTE Invoiced) by Nathalie Peyrard , you can review the following technical details about the eBook:
- Full Book Name: A Comprehensive Guide to HSMM: Theory, Software, and Advanced Extensions (ISTE Invoiced)
- Author Name: Nathalie Peyrard
- Book Genre: Non-Fiction, Educational
- Series Synopsis: “”
- ISBN # 9781836690351
- ASIN # 1836690355
- Edition Language: English
- Date of Publication: January 15, 2026
- File Name: A_Comprehensive_Guide_to_HSMM_-_Nathalie_Peyrard.epub, A_Comprehensive_Guide_to_HSMM_-_Nathalie_Peyrard.pdf
- EPUB Size: 1.5 MB
- PDF Size: 1.8 MB
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