{"id":"https://openalex.org/W4241592523","doi":"https://doi.org/10.1002/9781119229070.ch9","title":"Bayesian Analysis","display_name":"Bayesian Analysis","publication_year":2017,"publication_date":"2017-05-12","ids":{"openalex":"https://openalex.org/W4241592523","doi":"https://doi.org/10.1002/9781119229070.ch9"},"language":"en","primary_location":{"id":"doi:10.1002/9781119229070.ch9","doi":"https://doi.org/10.1002/9781119229070.ch9","is_oa":false,"landing_page_url":"https://doi.org/10.1002/9781119229070.ch9","pdf_url":null,"source":{"id":"https://openalex.org/S4306464293","display_name":"Wiley eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Differential Privacy","raw_type":"other"},"volume":{"id":"https://openalex.org/W2613985007","display_name":"Big Data and Differential Privacy"},"type":"book-chapter","is_traditional":true,"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/A5035496450","display_name":"Nii Attoh-Okine","orcid":"https://orcid.org/0000-0001-5328-5538","observed_orcids":["https://orcid.org/0000-0001-5328-5538"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nii O. Attoh-Okine","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5035496450"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"223"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9110999703407288,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9110999703407288,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.059300001710653305,"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.005900000222027302,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.8130000233650208},{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"approximate Bayesian computation","score":0.9570000171661377},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.9890000224113464},{"id":"https://openalex.org/keywords/rejection-sampling","display_name":"rejection sampling","score":0.8790000081062317},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"likelihood function","score":0.39399999380111694},{"id":"https://openalex.org/keywords/posterior-distribution","display_name":"posterior distribution","score":0.5139999985694885}],"concepts":[{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.8383018970489502},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7085921764373779},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.6397685408592224},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6016061305999756},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.5733203291893005},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.5606879591941833},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5414806008338928},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.5390055179595947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5364329218864441},{"id":"https://openalex.org/C71983512","wikidata":"https://www.wikidata.org/wiki/Q7915687","display_name":"Variable-order Bayesian network","level":4,"score":0.5303464531898499},{"id":"https://openalex.org/C149569020","wikidata":"https://www.wikidata.org/wiki/Q25098598","display_name":"Bayesian average","level":5,"score":0.4731796085834503},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.43093299865722656},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4304203987121582},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4167727828025818},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.41248440742492676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3777446448802948},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3774956464767456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3482389748096466},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2769022583961487},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.1304296851158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/9781119229070.ch9","doi":"https://doi.org/10.1002/9781119229070.ch9","is_oa":false,"landing_page_url":"https://doi.org/10.1002/9781119229070.ch9","pdf_url":null,"source":{"id":"https://openalex.org/S4306464293","display_name":"Wiley eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Differential Privacy","raw_type":"other"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W156765625","https://openalex.org/W1969761972","https://openalex.org/W2008640468","https://openalex.org/W2051734393","https://openalex.org/W2065734163","https://openalex.org/W2082850612","https://openalex.org/W2120679796","https://openalex.org/W2130034137","https://openalex.org/W2133770508","https://openalex.org/W2136336930","https://openalex.org/W2165618295","https://openalex.org/W2249868474","https://openalex.org/W2271902495","https://openalex.org/W4252279022"],"related_works":["https://openalex.org/W2950165273","https://openalex.org/W1546925913","https://openalex.org/W2733224243","https://openalex.org/W4416967950","https://openalex.org/W2486096584","https://openalex.org/W7095726423","https://openalex.org/W2888942907","https://openalex.org/W4247503545","https://openalex.org/W4220721385","https://openalex.org/W2950058074"],"abstract_inverted_index":{"In":[0,58,100],"statistical":[1],"decision-making,":[2],"there":[3],"are":[4,26],"two":[5],"main":[6],"approaches:":[7],"the":[8,11,19,23,34,47,65,72,78,92,122],"frequentist":[9],"and":[10,29],"Bayesian":[12,14,56,59,104,136],"approaches.":[13],"inference":[15],"is":[16,44,81,98,112],"conceived":[17],"under":[18],"assumption":[20],"that":[21,50],"all":[22],"unknown":[24],"parameters":[25],"random":[27],"variables":[28],"their":[30,37],"probability":[31,128],"distributions":[32],"denote":[33],"beliefs":[35],"about":[36],"values.":[38],"Markov":[39],"chain":[40],"Monte":[41],"Carlo":[42],"(MCMC)":[43],"one":[45,61],"of":[46,124,135],"computational":[48,93],"methods":[49],"have":[51],"been":[52],"applied":[53],"widely":[54],"in":[55,68,75,138],"inference.":[57],"statistics,":[60],"needs":[62],"to":[63,70,85,95,116],"evaluate":[64,96],"likelihood":[66,79],"function":[67,80],"order":[69],"obtain":[71],"posterior.":[73],"Unfortunately,":[74],"some":[76],"cases":[77],"either":[82],"mathematically":[83],"difficult":[84],"deal":[86],"with,":[87],"does":[88],"not":[89],"exist,":[90],"or":[91],"cost":[94],"it":[97],"expensive.":[99],"such":[101],"situations,":[102],"approximate":[103,114],"computation":[105],"(ABC),":[106],"otherwise":[107],"known":[108],"as":[109],"likelihood-free":[110],"computation,":[111],"an":[113],"method":[115],"use.":[117],"The":[118],"rejection":[119],"algorithm":[120],"involves":[121],"generation":[123],"samples":[125],"from":[126],"a":[127],"distribution.":[129],"This":[130],"chapter":[131],"shows":[132],"selected":[133],"examples":[134],"analysis":[137],"railway":[139],"track":[140],"engineering":[141],"applications.":[142]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-05-12T00:00:00"}