Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days.
Librería: Majestic Books, Hounslow, Reino Unido
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Librería: moluna, Greven, Alemania
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Idioma: Inglés
Publicado por John Wiley & Sons Dez 2025, 2025
ISBN 10: 1836690355 ISBN 13: 9781836690351
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 198,78
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Añadir al carritoBuch. Condición: Neu. Neuware - 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.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
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Añadir al carritoCondición: New. 2025. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
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Original o primera edición
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
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Añadir al carritoHardcover. Condición: new. Hardcover. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 272 pages. 6.14x0.63x9.21 inches. In Stock. This item is printed on demand.
Librería: CitiRetail, Stevenage, Reino Unido
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Añadir al carritoHardcover. Condición: new. Hardcover. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 222,12
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Añadir al carritoHardcover. Condición: new. Hardcover. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.