{"id":"https://openalex.org/W2121361281","doi":"https://doi.org/10.1002/nla.1916","title":"Comparison of strategies when building linear prediction models","display_name":"Comparison of strategies when building linear prediction models","publication_year":2013,"publication_date":"2013-12-13","ids":{"openalex":"https://openalex.org/W2121361281","doi":"https://doi.org/10.1002/nla.1916","mag":"2121361281"},"language":"en","primary_location":{"id":"doi:10.1002/nla.1916","is_oa":false,"landing_page_url":"https://doi.org/10.1002/nla.1916","pdf_url":null,"source":{"id":"https://openalex.org/S60324941","display_name":"Numerical Linear Algebra with Applications","issn_l":"1070-5325","issn":["1070-5325","1099-1506"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Numerical Linear Algebra with 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/A5046370525","display_name":"Wiebe R. Pestman","orcid":null},"institutions":[{"id":"https://openalex.org/I4104125","display_name":"Universidade Federal de Santa Catarina","ror":"https://ror.org/041akq887","country_code":"BR","type":"education","lineage":["https://openalex.org/I4104125"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Wiebe R. Pestman","raw_affiliation_strings":["Departamento de Matematica; Universidade Federal de Santa Catarina; Florianopolis SC Brazil"],"affiliations":[{"raw_affiliation_string":"Departamento de Matematica; Universidade Federal de Santa Catarina; Florianopolis SC Brazil","institution_ids":["https://openalex.org/I4104125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000339384","display_name":"Rolf H. H. Groenwold","orcid":"https://orcid.org/0000-0001-9238-6999"},"institutions":[{"id":"https://openalex.org/I3018483916","display_name":"University Medical Center Utrecht","ror":"https://ror.org/0575yy874","country_code":"NL","type":"funder","lineage":["https://openalex.org/I3018483916"]},{"id":"https://openalex.org/I193662353","display_name":"Utrecht University","ror":"https://ror.org/04pp8hn57","country_code":"NL","type":"education","lineage":["https://openalex.org/I193662353"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Rolf H.H. Groenwold","raw_affiliation_strings":["Department of Epidemiology; University Medical Center Utrecht; Utrecht The Netherlands","Department of Epidemiology, University Medical Center Utrecht, Utrecht, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Department of Epidemiology; University Medical Center Utrecht; Utrecht The Netherlands","institution_ids":["https://openalex.org/I3018483916","https://openalex.org/I193662353"]},{"raw_affiliation_string":"Department of Epidemiology, University Medical Center Utrecht, Utrecht, The Netherlands","institution_ids":["https://openalex.org/I3018483916"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037625836","display_name":"Steven Teerenstra","orcid":"https://orcid.org/0000-0003-4103-7451"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Steven Teerenstra","raw_affiliation_strings":["Department of Epidemiology; Radboud University; Nijmegen The Netherlands"],"affiliations":[{"raw_affiliation_string":"Department of Epidemiology; Radboud University; Nijmegen The Netherlands","institution_ids":["https://openalex.org/I145872427"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046370525"],"corresponding_institution_ids":["https://openalex.org/I4104125"],"apc_list":{"value":4430,"currency":"USD","value_usd":4430},"apc_paid":null,"fwci":0.3213,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66489877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"21","issue":"5","first_page":"618","last_page":"628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9936000108718872,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9936000108718872,"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":0.9902999997138977,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9804999828338623,"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/raw-data","display_name":"Raw data","score":0.5692931413650513},{"id":"https://openalex.org/keywords/model-building","display_name":"Model building","score":0.5280222296714783},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5279974937438965},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5203399658203125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5074788928031921},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4636932611465454},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44401803612709045},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.43003982305526733},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.41039788722991943},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3268822133541107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3145797848701477},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23471057415008545}],"concepts":[{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5692931413650513},{"id":"https://openalex.org/C189474733","wikidata":"https://www.wikidata.org/wiki/Q917912","display_name":"Model building","level":2,"score":0.5280222296714783},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5279974937438965},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5203399658203125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5074788928031921},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4636932611465454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44401803612709045},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.43003982305526733},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.41039788722991943},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3268822133541107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3145797848701477},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23471057415008545},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/nla.1916","is_oa":false,"landing_page_url":"https://doi.org/10.1002/nla.1916","pdf_url":null,"source":{"id":"https://openalex.org/S60324941","display_name":"Numerical Linear Algebra with Applications","issn_l":"1070-5325","issn":["1070-5325","1099-1506"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Numerical Linear Algebra with Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W48332454","https://openalex.org/W190001175","https://openalex.org/W1977393354","https://openalex.org/W2063261057","https://openalex.org/W2066815661","https://openalex.org/W2077562320","https://openalex.org/W2123485214","https://openalex.org/W2124700334","https://openalex.org/W3175417087","https://openalex.org/W4213286494","https://openalex.org/W4232359393","https://openalex.org/W4255298020"],"related_works":["https://openalex.org/W2076845124","https://openalex.org/W2183964146","https://openalex.org/W2379932303","https://openalex.org/W4300873085","https://openalex.org/W3147744369","https://openalex.org/W4241440711","https://openalex.org/W2062586268","https://openalex.org/W2605216517","https://openalex.org/W2289756541","https://openalex.org/W4289133130"],"abstract_inverted_index":{"In":[0,92],"statistical":[1],"and":[2],"biometric":[3],"sciences,":[4],"one":[5],"often":[6,59],"uses":[7],"predictive":[8,69],"linear":[9],"models.":[10,54],"The":[11],"initial":[12],"form":[13],"of":[14,24,30,61,88,97,107],"such":[15],"models":[16,41,57],"is":[17,101],"usually":[18],"obtained":[19,44],"by":[20],"fitting":[21],"the":[22,25,35,95,105],"coefficients":[23],"model":[26,89],"to":[27,34,51,63,67,79,85,103],"a":[28,86],"set":[29],"observed":[31],"data":[32],"according":[33],"classical":[36],"least":[37],"squares":[38],"method.":[39],"Newborn":[40],"that":[42],"are":[43,58],"in":[45],"this":[46,93],"way":[47],"will":[48],"be":[49,77],"referred":[50],"as":[52,66],"raw":[53,56,81],"Such":[55],"subject":[60],"efforts":[62],"improve":[64],"them":[65],"their":[68],"performance":[70,106],"on":[71],"external":[72],"datasets.":[73],"Several":[74],"methods":[75],"can":[76],"followed":[78],"fine-tune":[80],"models,":[82],"thus":[83],"leading":[84],"variety":[87],"building":[90,108],"strategies.":[91],"paper,":[94],"idea":[96],"so-called":[98],"victory":[99],"rates":[100],"introduced":[102],"compare":[104],"strategies":[109],"mutually.Copyright":[110],"\u00a9":[111],"2013":[112],"John":[113],"Wiley":[114],"&":[115],"Sons,":[116],"Ltd.":[117]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
