{"id":"https://openalex.org/W4415881432","doi":"https://doi.org/10.1080/00401706.2025.2565974","title":"Bayesian Inference: Theory, Methods, and Computations","display_name":"Bayesian Inference: Theory, Methods, and Computations","publication_year":2025,"publication_date":"2025-10-02","ids":{"openalex":"https://openalex.org/W4415881432","doi":"https://doi.org/10.1080/00401706.2025.2565974"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2025.2565974","is_oa":true,"landing_page_url":"https://doi.org/10.1080/00401706.2025.2565974","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/00401706.2025.2565974?needAccess=true","source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/00401706.2025.2565974?needAccess=true","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011987567","display_name":"Kazuhiko Kakamu","orcid":"https://orcid.org/0000-0003-1370-5520"},"institutions":[{"id":"https://openalex.org/I33858575","display_name":"Nagoya City University","ror":"https://ror.org/04wn7wc95","country_code":"JP","type":"education","lineage":["https://openalex.org/I33858575"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhiko Kakamu","raw_affiliation_strings":["Graduate School of Data Science, Nagoya City University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Data Science, Nagoya City University","institution_ids":["https://openalex.org/I33858575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035954014","display_name":"Shuangzhe Liu","orcid":"https://orcid.org/0000-0002-4858-2789"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shuangzhe Liu","raw_affiliation_strings":["Department of Science and Technology, University of Canberra"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Science and Technology, University of Canberra","institution_ids":["https://openalex.org/I188329596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16160669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"67","issue":"4","first_page":"728","last_page":"729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.0689999982714653,"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"}},"topics":[{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.0689999982714653,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.060100000351667404,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.05900000035762787,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6051999926567078},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5673999786376953},{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian computation","score":0.3160000145435333},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.28029999136924744},{"id":"https://openalex.org/keywords/bayesian-statistics","display_name":"Bayesian statistics","score":0.2797999978065491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6103000044822693},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6051999926567078},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5673999786376953},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5004000067710876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3546999990940094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33899998664855957},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.3160000145435333},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2944999933242798},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28369998931884766},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.2797999978065491},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00401706.2025.2565974","is_oa":true,"landing_page_url":"https://doi.org/10.1080/00401706.2025.2565974","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/00401706.2025.2565974?needAccess=true","source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1080/00401706.2025.2565974","is_oa":true,"landing_page_url":"https://doi.org/10.1080/00401706.2025.2565974","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/00401706.2025.2565974?needAccess=true","source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415881432.pdf","grobid_xml":"https://content.openalex.org/works/W4415881432.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W1579303078","https://openalex.org/W4248681815","https://openalex.org/W4256038730"],"related_works":[],"abstract_inverted_index":{"Bayesian":[0,24],"Inference:":[1],"Theory,":[2],"Methods,":[3],"and":[4,9],"Computations":[5],"by":[6],"Silvelyn":[7],"Zwanzig":[8],"Rauf":[10],"Ahmad":[11],"is":[12],"a":[13,18],"comprehensive":[14],"textbook":[15],"that":[16],"provides":[17],"rigorous":[19],"yet":[20],"accessible":[21],"treatment":[22],"of":[23],"inference.Chapter":[25],"...":[26]},"counts_by_year":[],"updated_date":"2026-06-14T06:11:07.267592","created_date":"2025-11-04T00:00:00"}