{"id":"https://openalex.org/W3123356524","doi":"https://doi.org/10.1561/2200000054","title":"Explicit-Duration Markov Switching Models","display_name":"Explicit-Duration Markov Switching Models","publication_year":2014,"publication_date":"2014-12-23","ids":{"openalex":"https://openalex.org/W3123356524","doi":"https://doi.org/10.1561/2200000054","mag":"3123356524"},"language":"en","primary_location":{"id":"doi:10.1561/2200000054","is_oa":false,"landing_page_url":"https://doi.org/10.1561/2200000054","pdf_url":null,"source":{"id":"https://openalex.org/S4210188176","display_name":"Foundations and Trends\u00ae in Machine Learning","issn_l":"1935-8237","issn":["1935-8237","1935-8245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318575","host_organization_name":"Now Publishers","host_organization_lineage":["https://openalex.org/P4310318575"],"host_organization_lineage_names":["Now Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Foundations and Trends\u00ae in Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1909.05800","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087675089","display_name":"Silvia Chiappa","orcid":"https://orcid.org/0000-0002-1882-6842"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":true,"raw_author_name":"Silvia Chiappa","raw_affiliation_strings":["Statistical Laboratory, University of Cambridge, Microsoft Research Cambridge ,","University of Cambridge and Microsoft Research Cambridge, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Statistical Laboratory, University of Cambridge, Microsoft Research Cambridge ,","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I1290206253"]},{"raw_affiliation_string":"University of Cambridge and Microsoft Research Cambridge, UK","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5087675089"],"corresponding_institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I241749","https://openalex.org/I4210164937"],"apc_list":null,"apc_paid":null,"fwci":0.8206,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.81033338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"7","issue":"6","first_page":"803","last_page":"886"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.699171781539917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6174392104148865},{"id":"https://openalex.org/keywords/reset","display_name":"Reset (finance)","score":0.6167787313461304},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5868956446647644},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5082597136497498},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.5064922571182251},{"id":"https://openalex.org/keywords/formalism","display_name":"Formalism (music)","score":0.505774974822998},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.49987006187438965},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.48619502782821655},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4478963017463684},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.4475204348564148},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.439831018447876},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34831732511520386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23905396461486816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20450258255004883}],"concepts":[{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.699171781539917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6174392104148865},{"id":"https://openalex.org/C2779795794","wikidata":"https://www.wikidata.org/wiki/Q7315343","display_name":"Reset (finance)","level":2,"score":0.6167787313461304},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5868956446647644},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5082597136497498},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.5064922571182251},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.505774974822998},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.49987006187438965},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.48619502782821655},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4478963017463684},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.4475204348564148},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.439831018447876},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34831732511520386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23905396461486816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20450258255004883},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C558565934","wikidata":"https://www.wikidata.org/wiki/Q2743","display_name":"Musical","level":2,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1561/2200000054","is_oa":false,"landing_page_url":"https://doi.org/10.1561/2200000054","pdf_url":null,"source":{"id":"https://openalex.org/S4210188176","display_name":"Foundations and Trends\u00ae in Machine Learning","issn_l":"1935-8237","issn":["1935-8237","1935-8245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318575","host_organization_name":"Now Publishers","host_organization_lineage":["https://openalex.org/P4310318575"],"host_organization_lineage_names":["Now Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Foundations and Trends\u00ae in Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1909.05800","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1909.05800","pdf_url":"https://arxiv.org/pdf/1909.05800","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1909.05800","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1909.05800","pdf_url":"https://arxiv.org/pdf/1909.05800","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3123356524.pdf","grobid_xml":"https://content.openalex.org/works/W3123356524.grobid-xml"},"referenced_works_count":71,"referenced_works":["https://openalex.org/W170433","https://openalex.org/W47906050","https://openalex.org/W564823429","https://openalex.org/W626418592","https://openalex.org/W1483365869","https://openalex.org/W1503398984","https://openalex.org/W1511986666","https://openalex.org/W1515824979","https://openalex.org/W1537786506","https://openalex.org/W1548405976","https://openalex.org/W1559065369","https://openalex.org/W1590183771","https://openalex.org/W1600276922","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1963828038","https://openalex.org/W1967042859","https://openalex.org/W1976551160","https://openalex.org/W1991485860","https://openalex.org/W1993657505","https://openalex.org/W2002272439","https://openalex.org/W2003590674","https://openalex.org/W2009570821","https://openalex.org/W2037799844","https://openalex.org/W2045893916","https://openalex.org/W2049633694","https://openalex.org/W2052441401","https://openalex.org/W2074812030","https://openalex.org/W2076618452","https://openalex.org/W2081239658","https://openalex.org/W2083393647","https://openalex.org/W2090394430","https://openalex.org/W2094227853","https://openalex.org/W2099867508","https://openalex.org/W2104791085","https://openalex.org/W2105080323","https://openalex.org/W2110935301","https://openalex.org/W2114165749","https://openalex.org/W2116764165","https://openalex.org/W2117515856","https://openalex.org/W2117853077","https://openalex.org/W2118292600","https://openalex.org/W2119545313","https://openalex.org/W2124397876","https://openalex.org/W2125344207","https://openalex.org/W2125838338","https://openalex.org/W2132350041","https://openalex.org/W2132630686","https://openalex.org/W2133332006","https://openalex.org/W2135939302","https://openalex.org/W2140890425","https://openalex.org/W2141572089","https://openalex.org/W2152042469","https://openalex.org/W2153331007","https://openalex.org/W2156633909","https://openalex.org/W2159080219","https://openalex.org/W2164597369","https://openalex.org/W2165300526","https://openalex.org/W2167015655","https://openalex.org/W2167746888","https://openalex.org/W2169089686","https://openalex.org/W2179055686","https://openalex.org/W2270719270","https://openalex.org/W2540151605","https://openalex.org/W2624120873","https://openalex.org/W3017131316","https://openalex.org/W4229936004","https://openalex.org/W4232023503","https://openalex.org/W4241640108","https://openalex.org/W4249072023","https://openalex.org/W4253573210"],"related_works":["https://openalex.org/W2082284720","https://openalex.org/W2116722627","https://openalex.org/W2537260108","https://openalex.org/W2379938888","https://openalex.org/W4233405330","https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W2194396582","https://openalex.org/W2799426416","https://openalex.org/W2566202039"],"abstract_inverted_index":{"Markov":[0,44],"switching":[1,30],"models":[2,6,103,108,121,185,228,246],"(MSMs)":[3],"are":[4,96,115,159],"probabilistic":[5],"that":[7,18,40,51,89,109,223],"employ":[8],"multiple":[9],"sets":[10],"of":[11,27,56,68,132,164,183,202,208,226],"parameters":[12],"to":[13,64,73,81,85,169,178,194,238,242,250],"describe":[14,180],"different":[15,25,138,151],"dynamic":[16],"regimes":[17,33],"a":[19,42,130,200,220],"time":[20,57],"series":[21],"may":[22],"exhibit":[23],"at":[24],"periods":[26],"time.":[28],"The":[29,157,190,215,232],"mechanism":[31],"between":[32,77],"is":[34,192,217],"controlled":[35],"by":[36,135],"unobserved":[37],"random":[38],"variables":[39,50,150],"form":[41],"first-order":[43],"chain.":[45],"Explicit-duration":[46],"MSMs":[47],"contain":[48],"additional":[49],"explicitly":[52],"model":[53,209],"the":[54,78,83,92,112,137,148,162,181,203,227],"distribution":[55],"spent":[58],"in":[59,145,147,206],"each":[60],"regime.":[61],"This":[62],"allows":[63,168],"define":[65],"duration":[66],"distributions":[67],"any":[69],"form,":[70],"but":[71],"also":[72],"impose":[74],"complex":[75,184],"dependence":[76,175],"observations":[79],"and":[80,172,176,186,212,229,247],"reset":[82,123],"dynamics":[84],"initial":[86],"conditions.":[87],"Models":[88],"focus":[90,110],"on":[91,111,198],"first":[93],"two":[94],"properties":[95],"most":[97,116,225],"commonly":[98,117],"known":[99,118],"as":[100,119],"hidden":[101],"semi-Markov":[102],"or":[104,122],"segment":[105],"models,":[106,166],"whilst":[107],"third":[113],"property":[114],"changepoint":[120],"models.":[124],"In":[125],"this":[126],"monograph,":[127],"we":[128],"provide":[129],"description":[131],"explicitduration":[133],"modelling":[134],"categorizing":[136],"approaches":[139,158],"into":[140],"three":[141,204],"groups,":[142],"which":[143,167],"differ":[144],"encoding":[146],"explicit-duration":[149],"information":[152],"about":[153,244],"regime":[154],"change/reset":[155],"boundaries.":[156],"described":[160],"using":[161],"formalism":[163],"graphical":[165],"graphically":[170],"represent":[171],"assess":[173],"statistical":[174],"therefore":[177],"easily":[179],"structure":[182,210],"derive":[187],"inference":[188,213],"routines.":[189],"presentation":[191],"intended":[193],"be":[195,236],"pedagogical,":[196],"focusing":[197],"providing":[199],"characterization":[201],"groups":[205],"terms":[207],"constraints":[211],"properties.":[214],"monograph":[216],"supplemented":[218],"with":[219],"software":[221],"package":[222],"contains":[224],"examples":[230],"described1.":[231],"material":[233],"presented":[234],"should":[235],"useful":[237],"both":[239],"researchers":[240,248],"wishing":[241,249],"learn":[243],"these":[245],"develop":[251],"them":[252],"further.":[253]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}
