{"id":"https://openalex.org/W2133622633","doi":"https://doi.org/10.1080/03610910701855005","title":"Choosing Principal Components: A New Graphical Method Based on Bayesian Model Selection","display_name":"Choosing Principal Components: A New Graphical Method Based on Bayesian Model Selection","publication_year":2008,"publication_date":"2008-04-14","ids":{"openalex":"https://openalex.org/W2133622633","doi":"https://doi.org/10.1080/03610910701855005","mag":"2133622633"},"language":"en","primary_location":{"id":"doi:10.1080/03610910701855005","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910701855005","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","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/A5076875226","display_name":"Philipp Auer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119100","display_name":"Munich Security Conference","ror":"https://ror.org/02jch6d72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I4210119100"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Philipp Auer","raw_affiliation_strings":["M\u00fcnchener R\u00fcckversicherungs-Gesellschaft, Koniginstrasse 107","M\u00fcnchener R\u00fcckversicherungs-Gesellschaft, Koniginstrasse 107 ,"],"affiliations":[{"raw_affiliation_string":"M\u00fcnchener R\u00fcckversicherungs-Gesellschaft, Koniginstrasse 107","institution_ids":["https://openalex.org/I4210119100"]},{"raw_affiliation_string":"M\u00fcnchener R\u00fcckversicherungs-Gesellschaft, Koniginstrasse 107 ,","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001528444","display_name":"Daniel Gervini","orcid":"https://orcid.org/0000-0003-2655-0337"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daniel Gervini","raw_affiliation_strings":["University of Wisconsin\u2013Milwaukee","Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin\u2013Milwaukee","institution_ids":["https://openalex.org/I43579087"]},{"raw_affiliation_string":"Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA","institution_ids":["https://openalex.org/I43579087"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001528444"],"corresponding_institution_ids":["https://openalex.org/I43579087"],"apc_list":null,"apc_paid":null,"fwci":0.6074,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.72777195,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"37","issue":"5","first_page":"962","last_page":"977"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9975000023841858,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9975000023841858,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T13141","display_name":"Statistical Methods and Applications","score":0.9814000129699707,"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/computer-science","display_name":"Computer science","score":0.6194170713424683},{"id":"https://openalex.org/keywords/plot","display_name":"Plot (graphics)","score":0.569146990776062},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5487096309661865},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5287810564041138},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5235940217971802},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.49855685234069824},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.49697330594062805},{"id":"https://openalex.org/keywords/principal","display_name":"Principal (computer security)","score":0.4913713037967682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47892507910728455},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4726085960865021},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4696813225746155},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4675397276878357},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4612523317337036},{"id":"https://openalex.org/keywords/bayes-factor","display_name":"Bayes factor","score":0.45449721813201904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4447001814842224},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3898913264274597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29613620042800903},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20437803864479065}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6194170713424683},{"id":"https://openalex.org/C167651023","wikidata":"https://www.wikidata.org/wiki/Q1474611","display_name":"Plot (graphics)","level":2,"score":0.569146990776062},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5487096309661865},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5287810564041138},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5235940217971802},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.49855685234069824},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.49697330594062805},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.4913713037967682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47892507910728455},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4726085960865021},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4696813225746155},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4675397276878357},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4612523317337036},{"id":"https://openalex.org/C142291917","wikidata":"https://www.wikidata.org/wiki/Q4165283","display_name":"Bayes factor","level":4,"score":0.45449721813201904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4447001814842224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3898913264274597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29613620042800903},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20437803864479065},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910701855005","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910701855005","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W184430818","https://openalex.org/W1480376833","https://openalex.org/W1502461990","https://openalex.org/W1554944419","https://openalex.org/W1965555084","https://openalex.org/W2005051528","https://openalex.org/W2007356270","https://openalex.org/W2071128523","https://openalex.org/W2133097426","https://openalex.org/W2160172778","https://openalex.org/W2165918462","https://openalex.org/W2171033594","https://openalex.org/W2313636552","https://openalex.org/W3099514962","https://openalex.org/W4205767108","https://openalex.org/W4235611253","https://openalex.org/W4250857377","https://openalex.org/W4256511286"],"related_works":["https://openalex.org/W4235847508","https://openalex.org/W1991984435","https://openalex.org/W2025014919","https://openalex.org/W2948401447","https://openalex.org/W3125503411","https://openalex.org/W2343819364","https://openalex.org/W4388289949","https://openalex.org/W2521530597","https://openalex.org/W217340113","https://openalex.org/W2133205540"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"article":[2],"approaches":[3],"the":[4,35,41,50,54,70],"problem":[5],"of":[6,31,43,53],"selecting":[7],"significant":[8,44],"principal":[9],"components":[10,45],"from":[11],"a":[12,22],"Bayesian":[13],"model":[14],"selection":[15],"perspective.":[16],"The":[17],"resulting":[18],"Bayes":[19],"rule":[20],"provides":[21,65],"simple":[23],"graphical":[24],"technique":[25],"that":[26,63],"can":[27],"be":[28],"used":[29],"instead":[30],"(or":[32],"together":[33],"with)":[34],"popular":[36],"scree":[37,71],"plot":[38,72],"to":[39,46],"determine":[40],"number":[42],"retain.":[47],"We":[48],"study":[49],"theoretical":[51],"properties":[52],"new":[55],"method":[56],"and":[57,61],"show,":[58],"by":[59],"examples":[60],"simulation,":[62],"it":[64],"more":[66],"clear-cut":[67],"answers":[68],"than":[69],"in":[73],"many":[74],"interesting":[75],"situations.":[76],"Keywords:":[77],"Dimension":[78],"reductionFactor":[79],"analysisScree":[80],"plotSingular":[81],"value":[82],"decompositionMathematics":[83],"Subject":[84],"Classification:":[85],"Primary":[86],"62H25Secondary":[87],"62-09":[88]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-02-08T09:19:03.324500","created_date":"2025-10-10T00:00:00"}
