{"product_id":"9781836690351","title":"A Comprehensive Guide to HSMM Theory, Software, and Advanced Extensions","description":"\u003ch3\u003eISTE Invoiced\u003c\/h3\u003e\u003ch1\u003eA Comprehensive Guide to HSMM\u003c\/h1\u003e\u003ch2\u003eTheory, Software, and Advanced Extensions\u003c\/h2\u003e\u003ch3\u003eNathalie Peyrard | Benoîte de Saporta\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Probability \u0026amp; Statistics \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003e\u003cb\u003eHidden 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.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eA Comprehensive Guide to HSMM\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eThis 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.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e \u003cp\u003e\u003cb\u003eNathalie Peyrard\u003c\/b\u003e is Senior Scientist at INRAE, Toulouse, France. Her research includes computational statistics in models with latent variables, with applications in ecology.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eBenoîte de Saporta\u003c\/b\u003e is Professor of Applied Mathematics at the University of Montpellier, France. Her research includes applied probability (Markov processes, optimal stochastic control) and statistics (inference for partially hidden processes).\u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e15 January 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley-ISTE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781836690351\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e272\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e23.52\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44775298826380,"sku":"9781836690351","price":153.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781836690351_757d3ee1-52db-4215-8e03-8cece3015889.jpg?v=1780107114","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781836690351","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}