{"id":"https://openalex.org/W4252203934","doi":"https://doi.org/10.1017/s0021900200012572","title":"On Binomial Observations of Continuous-Time Markovian Population Models","display_name":"On Binomial Observations of Continuous-Time Markovian Population Models","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W4252203934","doi":"https://doi.org/10.1017/s0021900200012572"},"language":"en","primary_location":{"id":"doi:10.1017/s0021900200012572","is_oa":false,"landing_page_url":"http://doi.org/10.1017/s0021900200012572","pdf_url":null,"source":{"id":"https://openalex.org/S160779208","display_name":"Journal of Applied Probability","issn_l":"0021-9002","issn":["0021-9002","1475-6072"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Probability","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063747483","display_name":"Nigel Bean","orcid":"https://orcid.org/0000-0002-5351-3104"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"N. G. Bean","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045670674","display_name":"Robert J. Elliott","orcid":"https://orcid.org/0000-0002-5486-6999"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. Elliott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074205731","display_name":"Ali Eshragh","orcid":"https://orcid.org/0000-0002-0874-1626"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Eshragh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5026776788","display_name":"Joshua V. Ross","orcid":"https://orcid.org/0000-0002-9918-8167"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"J. V. Ross","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.30169361,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"52","issue":"02","first_page":"457","last_page":"472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11152","display_name":"Stochastic processes and statistical mechanics","score":0.9674999713897705,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11152","display_name":"Stochastic processes and statistical mechanics","score":0.9674999713897705,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10482","display_name":"Mathematical and Theoretical Epidemiology and Ecology Models","score":0.947700023651123,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9186999797821045,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7452616691589355},{"id":"https://openalex.org/keywords/binomial-distribution","display_name":"Binomial distribution","score":0.624254584312439},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5888722538948059},{"id":"https://openalex.org/keywords/binomial-approximation","display_name":"Binomial approximation","score":0.5664834976196289},{"id":"https://openalex.org/keywords/binomial","display_name":"Binomial (polynomial)","score":0.5631294846534729},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"Conditional probability","score":0.5586975812911987},{"id":"https://openalex.org/keywords/regular-conditional-probability","display_name":"Regular conditional probability","score":0.5492022037506104},{"id":"https://openalex.org/keywords/law-of-total-probability","display_name":"Law of total probability","score":0.535832405090332},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.5043081045150757},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4266572594642639},{"id":"https://openalex.org/keywords/probability-mass-function","display_name":"Probability mass function","score":0.35799768567085266},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3273601531982422},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.26775017380714417},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.1443130373954773},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.1430777907371521},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.125392884016037}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7452616691589355},{"id":"https://openalex.org/C41054675","wikidata":"https://www.wikidata.org/wiki/Q185547","display_name":"Binomial distribution","level":2,"score":0.624254584312439},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5888722538948059},{"id":"https://openalex.org/C9209722","wikidata":"https://www.wikidata.org/wiki/Q4914487","display_name":"Binomial approximation","level":4,"score":0.5664834976196289},{"id":"https://openalex.org/C2781315470","wikidata":"https://www.wikidata.org/wiki/Q193623","display_name":"Binomial (polynomial)","level":2,"score":0.5631294846534729},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.5586975812911987},{"id":"https://openalex.org/C103982235","wikidata":"https://www.wikidata.org/wiki/Q7309594","display_name":"Regular conditional probability","level":4,"score":0.5492022037506104},{"id":"https://openalex.org/C49698424","wikidata":"https://www.wikidata.org/wiki/Q1989192","display_name":"Law of total probability","level":4,"score":0.535832405090332},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.5043081045150757},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4266572594642639},{"id":"https://openalex.org/C197096303","wikidata":"https://www.wikidata.org/wiki/Q869887","display_name":"Probability mass function","level":3,"score":0.35799768567085266},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3273601531982422},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.26775017380714417},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1443130373954773},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.1430777907371521},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.125392884016037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s0021900200012572","is_oa":false,"landing_page_url":"http://doi.org/10.1017/s0021900200012572","pdf_url":null,"source":{"id":"https://openalex.org/S160779208","display_name":"Journal of Applied Probability","issn_l":"0021-9002","issn":["0021-9002","1475-6072"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Probability","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1981056595","https://openalex.org/W1995757542","https://openalex.org/W2000032310","https://openalex.org/W2007373589","https://openalex.org/W2027828392","https://openalex.org/W2090298372","https://openalex.org/W2108678981","https://openalex.org/W2122155256","https://openalex.org/W2123786618","https://openalex.org/W2131771450","https://openalex.org/W2132192754","https://openalex.org/W2135869163","https://openalex.org/W2141937743","https://openalex.org/W2147659356"],"related_works":["https://openalex.org/W1523756637","https://openalex.org/W4248569664","https://openalex.org/W2518961608","https://openalex.org/W4235623166","https://openalex.org/W23363913","https://openalex.org/W193767348","https://openalex.org/W3044665550","https://openalex.org/W4224306311","https://openalex.org/W1563223341","https://openalex.org/W4252203934"],"abstract_inverted_index":{"In":[0],"this":[1,38],"paper":[2],"we":[3,40],"consider":[4],"a":[5,32,56,63],"class":[6],"of":[7,14,26,34,48,58,74,89,107],"stochastic":[8,91],"processes":[9],"based":[10],"on":[11],"binomial":[12,29,35,59,96,105],"observations":[13,106],"continuous-time,":[15],"Markovian":[16,52],"population":[17,53],"models.":[18],"We":[19,98],"derive":[20],"the":[21,27,43,49,72,79,84,90,95,108],"conditional":[22,44,64],"probability":[23,45,76],"mass":[24,46],"function":[25,47],"next":[28],"observation":[30],"given":[31,55],"set":[33,57],"observations.":[36,97],"For":[37],"purpose,":[39],"first":[41],"find":[42,78],"underlying":[50],"continuous-time":[51],"model,":[54],"observations,":[60],"by":[61,94],"exploiting":[62],"Bayes'":[65],"theorem":[66],"from":[67],"filtering,":[68],"and":[69],"then":[70],"use":[71],"law":[73],"total":[75],"to":[77,102],"former.":[80],"This":[81],"result":[82],"paves":[83],"way":[85],"for":[86],"further":[87],"study":[88],"process":[92,111],"introduced":[93],"utilize":[99],"our":[100],"results":[101],"show":[103],"that":[104],"simple":[109],"birth":[110],"are":[112],"non-Markovian.":[113]},"counts_by_year":[{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}