{"id":"https://openalex.org/W2787870313","doi":"https://doi.org/10.3233/mas-170418","title":"An assessment of predictive performance of Zellner\u2019s g-priors in Bayesian model averaging","display_name":"An assessment of predictive performance of Zellner\u2019s g-priors in Bayesian model averaging","publication_year":2018,"publication_date":"2018-02-06","ids":{"openalex":"https://openalex.org/W2787870313","doi":"https://doi.org/10.3233/mas-170418","mag":"2787870313"},"language":"en","primary_location":{"id":"doi:10.3233/mas-170418","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-170418","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","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/A5041340854","display_name":"Rotimi Ogundeji","orcid":null},"institutions":[{"id":"https://openalex.org/I197610006","display_name":"University of Lagos","ror":"https://ror.org/05rk03822","country_code":"NG","type":"education","lineage":["https://openalex.org/I197610006"]}],"countries":["NG"],"is_corresponding":true,"raw_author_name":"Rotimi Ogundeji","raw_affiliation_strings":["Department of Mathematics, University of Lagos, Nigeria"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Lagos, Nigeria","institution_ids":["https://openalex.org/I197610006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019179786","display_name":"Ismaila Adeleke","orcid":"https://orcid.org/0000-0001-8304-6159"},"institutions":[{"id":"https://openalex.org/I197610006","display_name":"University of Lagos","ror":"https://ror.org/05rk03822","country_code":"NG","type":"education","lineage":["https://openalex.org/I197610006"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Ismaila Adeleke","raw_affiliation_strings":["Department of Actuarial Science and Insurance, University of Lagos, Nigeria"],"affiliations":[{"raw_affiliation_string":"Department of Actuarial Science and Insurance, University of Lagos, Nigeria","institution_ids":["https://openalex.org/I197610006"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027731895","display_name":"Ray Okafor","orcid":null},"institutions":[{"id":"https://openalex.org/I197610006","display_name":"University of Lagos","ror":"https://ror.org/05rk03822","country_code":"NG","type":"education","lineage":["https://openalex.org/I197610006"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Ray Okafor","raw_affiliation_strings":["Department of Mathematics, University of Lagos, Nigeria"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Lagos, Nigeria","institution_ids":["https://openalex.org/I197610006"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041340854"],"corresponding_institution_ids":["https://openalex.org/I197610006"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.020856,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"1","first_page":"63","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9991000294685364,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9991000294685364,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9984999895095825,"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":0.9983999729156494,"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/prior-probability","display_name":"Prior probability","score":0.8986889123916626},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6787088513374329},{"id":"https://openalex.org/keywords/posterior-predictive-distribution","display_name":"Posterior predictive distribution","score":0.5655136108398438},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.537310004234314},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5182387828826904},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5157201886177063},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.5144469738006592},{"id":"https://openalex.org/keywords/bayesian-linear-regression","display_name":"Bayesian linear regression","score":0.5129715800285339},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.475538969039917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4706308841705322},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.45832809805870056},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4116988182067871}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8986889123916626},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6787088513374329},{"id":"https://openalex.org/C83247935","wikidata":"https://www.wikidata.org/wiki/Q7234227","display_name":"Posterior predictive distribution","level":5,"score":0.5655136108398438},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.537310004234314},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5182387828826904},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5157201886177063},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.5144469738006592},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.5129715800285339},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.475538969039917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4706308841705322},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.45832809805870056},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4116988182067871},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/mas-170418","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-170418","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.6200000047683716,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1500470240","https://openalex.org/W1541705153","https://openalex.org/W1603903339","https://openalex.org/W1666386643","https://openalex.org/W1800261609","https://openalex.org/W1953770855","https://openalex.org/W1972631921","https://openalex.org/W1977944427","https://openalex.org/W1986783130","https://openalex.org/W2020389170","https://openalex.org/W2044633735","https://openalex.org/W2057331441","https://openalex.org/W2064606425","https://openalex.org/W2085890860","https://openalex.org/W2108207895","https://openalex.org/W2114125162","https://openalex.org/W2120695425","https://openalex.org/W2135728169","https://openalex.org/W2139606141","https://openalex.org/W2145860152","https://openalex.org/W2152933101","https://openalex.org/W2171929283","https://openalex.org/W2397712474","https://openalex.org/W2491861244","https://openalex.org/W2530261910","https://openalex.org/W3124139837","https://openalex.org/W3214323364","https://openalex.org/W4211177544","https://openalex.org/W4250518393","https://openalex.org/W6628484549","https://openalex.org/W6666745690","https://openalex.org/W6677205471","https://openalex.org/W6728924094","https://openalex.org/W6804231292","https://openalex.org/W7036059017"],"related_works":["https://openalex.org/W2520428977","https://openalex.org/W2032055373","https://openalex.org/W2042714036","https://openalex.org/W2365456432","https://openalex.org/W1977596751","https://openalex.org/W2007093222","https://openalex.org/W4244676996","https://openalex.org/W69468016","https://openalex.org/W173785400","https://openalex.org/W4321613659"],"abstract_inverted_index":{"When":[0],"making":[1],"predictions":[2],"and":[3,70,109,129,155,177,200,239,268],"inferences,":[4],"data":[5,68,176,182,215,221],"analysts":[6],"are":[7,85,148],"often":[8],"faced":[9],"with":[10,135,245],"the":[11,15,58,76,89,166,193,197,204,209,212,220,231,250,263,273],"challenge":[12],"of":[13,24,27,57,60,78,91,99,144,162,168,196,265,275],"selecting":[14],"best":[16],"model":[17,33,36,50,72,79,82,113],"among":[18],"competing":[19],"models":[20],"as":[21,222],"a":[22,40,97,256],"result":[23],"large":[25,32],"number":[26],"regressors":[28],"that":[29,227,261,271],"cumulate":[30],"into":[31],"space.":[34],"Bayesian":[35,54,112,124,259],"averaging":[37],"(BMA)":[38],"is":[39,127],"technique":[41],"designed":[42],"to":[43,88,165,191],"help":[44],"account":[45],"for":[46,120,203,208],"uncertainty":[47,80],"inherent":[48],"in":[49,67,75,107,111,123,139],"selection":[51,83],"process.":[52],"In":[53],"analysis,":[55],"issues":[56],"choice":[59,167],"prior":[61,92,266],"distribution":[62,187],"have":[63],"been":[64],"quite":[65],"delicate":[66],"analysis":[69],"posterior":[71,163],"probabilities":[73],"(PMP)":[74],"context":[77],"under":[81,228],"process":[84],"typically":[86],"sensititve":[87],"specification":[90,119],"distribution.":[93],"This":[94],"research":[95],"identified":[96,246],"set":[98],"eleven":[100],"candidate":[101],"default":[102],"priors":[103],"(Zellner\u2019s":[104],"g-priors)":[105],"prominent":[106],"literature":[108],"applicable":[110],"averaging.":[114],"A":[115],"new":[116,232,253],"robust":[117],"g-prior":[118,137,146,170,198,233,247,254],"regression":[121],"coefficients":[122],"Model":[125],"Averaging":[126],"investigated":[128],"its":[130],"predictive":[131,142,152,194,241,269],"performance":[132,195],"assessed":[133,149],"along":[134],"other":[136],"structures":[138,147,171,199,248],"literature.":[140,251],"The":[141,160,180,252],"abilities":[143],"these":[145,169],"using":[150,174,219],"log":[151,156],"scores":[153],"(LPS)":[154],"maximum":[157],"likelihood":[158],"(LML).":[159],"sensitivity":[161],"results":[164],"was":[172],"demonstrated":[173],"simulated":[175,181],"real-life":[178],"data.":[179],"obtained":[183],"from":[184,249],"multivariate":[185],"normal":[186],"were":[188,216],"first":[189],"used":[190],"demonstrate":[192],"later":[201],"contaminated":[202],"same":[205,210],"purpose.":[206],"Similarly":[207],"purpose,":[211],"real":[213],"life":[214],"normalized":[217],"before":[218],"obtained.":[223],"Empirical":[224],"findings":[225],"reveal":[226],"different":[229],"conditions,":[230],"structure":[234],"exhibited":[235],"robust,":[236],"equally":[237],"competitive":[238],"consistent":[240],"ability":[242],"when":[243],"compared":[244],"offers":[255],"sound,":[257],"fully":[258],"approach":[260],"features":[262],"virtues":[264],"input":[267],"gains":[270],"minimise":[272],"risk":[274],"misspecification.":[276]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
