{"id":"https://openalex.org/W2963400661","doi":"https://doi.org/10.1007/s11222-018-9841-3","title":"Improving the efficiency and robustness of nested sampling using posterior repartitioning","display_name":"Improving the efficiency and robustness of nested sampling using posterior repartitioning","publication_year":2018,"publication_date":"2018-11-18","ids":{"openalex":"https://openalex.org/W2963400661","doi":"https://doi.org/10.1007/s11222-018-9841-3","mag":"2963400661"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-018-9841-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9841-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9841-3.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9841-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100329939","display_name":"Xi Chen","orcid":"https://orcid.org/0000-0002-3577-3308"},"institutions":[{"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"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xi Chen","raw_affiliation_strings":["Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK"],"raw_orcid":"https://orcid.org/0000-0002-3577-3308","affiliations":[{"raw_affiliation_string":"Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037021885","display_name":"M. P. Hobson","orcid":"https://orcid.org/0000-0002-0384-0182"},"institutions":[{"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"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Michael Hobson","raw_affiliation_strings":["Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074019305","display_name":"Saptarshi Das","orcid":"https://orcid.org/0000-0002-8394-5303"},"institutions":[{"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"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Saptarshi Das","raw_affiliation_strings":["Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014487922","display_name":"Paul Gelderblom","orcid":null},"institutions":[{"id":"https://openalex.org/I7923278","display_name":"Shell (Netherlands)","ror":"https://ror.org/00b5m4j81","country_code":"NL","type":"company","lineage":["https://openalex.org/I7923278"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Paul Gelderblom","raw_affiliation_strings":["Shell Global Solutions International BV, Amsterdam, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shell Global Solutions International BV, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I7923278"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100329939"],"corresponding_institution_ids":["https://openalex.org/I241749"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.2108,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.58743691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"29","issue":"4","first_page":"835","last_page":"850"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9952999949455261,"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/prior-probability","display_name":"Prior probability","score":0.8067415952682495},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7127115726470947},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.6433800458908081},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6129071712493896},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.611562967300415},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5265764594078064},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5123277902603149},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.49965381622314453},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4433932900428772},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.43006786704063416},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42768219113349915},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4267258644104004},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.41032010316848755},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38342034816741943},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3710355758666992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20780816674232483}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8067415952682495},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7127115726470947},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.6433800458908081},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6129071712493896},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.611562967300415},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5265764594078064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5123277902603149},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.49965381622314453},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4433932900428772},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.43006786704063416},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42768219113349915},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4267258644104004},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.41032010316848755},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38342034816741943},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3710355758666992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20780816674232483},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11222-018-9841-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9841-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9841-3.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmh:oai:ore.exeter.ac.uk:10871/34839","is_oa":true,"landing_page_url":"http://hdl.handle.net/10871/34839","pdf_url":null,"source":{"id":"https://openalex.org/S4306401998","display_name":"Open Research Exeter (University of Exeter)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I23923803","host_organization_name":"University of Exeter","host_organization_lineage":["https://openalex.org/I23923803"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1007/s11222-018-9841-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9841-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9841-3.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320273","display_name":"University of Cambridge","ror":"https://ror.org/013meh722"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963400661.pdf","grobid_xml":"https://content.openalex.org/works/W2963400661.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W280536263","https://openalex.org/W1487139063","https://openalex.org/W1513873506","https://openalex.org/W1607198972","https://openalex.org/W1663973292","https://openalex.org/W1836665496","https://openalex.org/W1839094326","https://openalex.org/W1886713477","https://openalex.org/W1982798554","https://openalex.org/W1990119892","https://openalex.org/W2015731569","https://openalex.org/W2092194717","https://openalex.org/W2107892672","https://openalex.org/W2132481658","https://openalex.org/W2161130145","https://openalex.org/W2217402295","https://openalex.org/W2602422862","https://openalex.org/W2962947173","https://openalex.org/W3104188978","https://openalex.org/W3140968660","https://openalex.org/W6968001735"],"related_works":["https://openalex.org/W2015518264","https://openalex.org/W2135187896","https://openalex.org/W2562263695","https://openalex.org/W3160546271","https://openalex.org/W2147201983","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W1718066205","https://openalex.org/W3006565005","https://openalex.org/W2964314781"],"abstract_inverted_index":{"In":[0,23],"real-world":[1,80],"Bayesian":[2],"inference":[3],"applications,":[4,81],"prior":[5,38,68,92,135],"assumptions":[6],"regarding":[7],"the":[8,26,33,36,48,67,94,104,108,128,132,143,152,155,165,179],"parameters":[9,109],"of":[10,15,35,47,96,100,107,110,154,181],"interest":[11,111],"may":[12,112],"be":[13,75],"unrepresentative":[14,182],"their":[16,138],"actual":[17],"values":[18,106],"for":[19,82,102,123,174],"a":[20,89,97,118,169],"given":[21],"dataset.":[22],"particular,":[24],"if":[25],"likelihood":[27,133],"is":[28,158],"concentrated":[29],"far":[30],"out":[31],"in":[32,70,79],"wings":[34],"assumed":[37],"distribution,":[39],"this":[40],"can":[41],"lead":[42],"to":[43,87,177],"extremely":[44],"inefficient":[45],"exploration":[46],"resulting":[49],"posterior":[50,119,144],"by":[51,130],"nested":[52],"sampling":[53],"(NS)":[54],"algorithms,":[55,125],"with":[56],"unnecessarily":[57],"high":[58],"associated":[59],"computational":[60],"costs.":[61],"Simple":[62],"solutions":[63],"such":[64,71],"as":[65],"broadening":[66],"range":[69],"cases":[72],"might":[73],"not":[74],"appropriate":[76],"or":[77],"possible":[78],"example":[83],"when":[84],"one":[85],"wishes":[86],"assume":[88],"single":[90],"standardised":[91],"across":[93],"analysis":[95],"large":[98],"number":[99],"datasets":[101],"which":[103,126],"true":[105],"vary.":[113],"This":[114],"work":[115],"therefore":[116],"introduces":[117],"repartitioning":[120],"(PR)":[121],"method":[122,167],"NS":[124,156,175],"addresses":[127],"problem":[129],"redefining":[131],"and":[134,146],"while":[136],"keeping":[137],"product":[139],"fixed,":[140],"so":[141],"that":[142,164],"inferences":[145],"evidence":[147],"estimates":[148],"remain":[149],"unchanged":[150],"but":[151],"efficiency":[153],"process":[157],"significantly":[159],"increased.":[160],"Numerical":[161],"results":[162],"show":[163],"PR":[166],"provides":[168],"simple":[170],"yet":[171],"powerful":[172],"refinement":[173],"algorithms":[176],"address":[178],"issue":[180],"priors.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}