{"id":"https://openalex.org/W1974180009","doi":"https://doi.org/10.1007/s11222-009-9158-3","title":"Bayesian regularisation in structured additive regression: a\u00a0unifying perspective on shrinkage, smoothing and predictor selection","display_name":"Bayesian regularisation in structured additive regression: a\u00a0unifying perspective on shrinkage, smoothing and predictor selection","publication_year":2009,"publication_date":"2009-11-20","ids":{"openalex":"https://openalex.org/W1974180009","doi":"https://doi.org/10.1007/s11222-009-9158-3","mag":"1974180009"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-009-9158-3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11222-009-9158-3","pdf_url":null,"source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://resolver.sub.uni-goettingen.de/purl?gro-2/5979","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088639152","display_name":"Ludwig Fahrmeir","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ludwig Fahrmeir","raw_affiliation_strings":["Department of Statistics, Ludwig-Maximilians-University, Munich, Germany","Department of Statistics, Ludwig-Maximilians Univ. Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Ludwig-Maximilians-University, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"Department of Statistics, Ludwig-Maximilians Univ. Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009871877","display_name":"Thomas Kneib","orcid":"https://orcid.org/0000-0003-3390-0972"},"institutions":[{"id":"https://openalex.org/I129877168","display_name":"Carl von Ossietzky Universit\u00e4t Oldenburg","ror":"https://ror.org/033n9gh91","country_code":"DE","type":"education","lineage":["https://openalex.org/I129877168"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Thomas Kneib","raw_affiliation_strings":["Department of Mathematics, Carl von Ossietzky University, Oldenburg, Germany","Department of Mathematics, Carl von Ossietzky University, Oldenburg, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Carl von Ossietzky University, Oldenburg, Germany","institution_ids":["https://openalex.org/I129877168"]},{"raw_affiliation_string":"Department of Mathematics, Carl von Ossietzky University, Oldenburg, Germany#TAB#","institution_ids":["https://openalex.org/I129877168"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015678234","display_name":"Susanne Konrath","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Susanne Konrath","raw_affiliation_strings":["Department of Statistics, Ludwig-Maximilians-University, Munich, Germany","Department of Statistics, Ludwig-Maximilians Univ. Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Ludwig-Maximilians-University, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"Department of Statistics, Ludwig-Maximilians Univ. Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009871877"],"corresponding_institution_ids":["https://openalex.org/I129877168"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":null,"fwci":5.2288,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.95710599,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"20","issue":"2","first_page":"203","last_page":"219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9987000226974487,"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":0.9987000226974487,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9896000027656555,"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":0.9886999726295471,"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":0.8697003126144409},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5975766777992249},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5559308528900146},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5477536916732788},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5425160527229309},{"id":"https://openalex.org/keywords/bayesian-linear-regression","display_name":"Bayesian linear regression","score":0.524412989616394},{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.5062269568443298},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5030636191368103},{"id":"https://openalex.org/keywords/shrinkage-estimator","display_name":"Shrinkage estimator","score":0.4912394881248474},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4499923288822174},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.42951348423957825},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.42404791712760925},{"id":"https://openalex.org/keywords/nonparametric-regression","display_name":"Nonparametric regression","score":0.41707533597946167},{"id":"https://openalex.org/keywords/additive-model","display_name":"Additive model","score":0.4161831736564636},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3542925715446472},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32898128032684326},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.31284379959106445},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.2634243369102478},{"id":"https://openalex.org/keywords/efficient-estimator","display_name":"Efficient estimator","score":0.10023567080497742}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8697003126144409},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5975766777992249},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5559308528900146},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5477536916732788},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5425160527229309},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.524412989616394},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.5062269568443298},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5030636191368103},{"id":"https://openalex.org/C102592046","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage estimator","level":5,"score":0.4912394881248474},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4499923288822174},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.42951348423957825},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.42404791712760925},{"id":"https://openalex.org/C74127309","wikidata":"https://www.wikidata.org/wiki/Q3455886","display_name":"Nonparametric regression","level":3,"score":0.41707533597946167},{"id":"https://openalex.org/C203223496","wikidata":"https://www.wikidata.org/wiki/Q4681344","display_name":"Additive model","level":2,"score":0.4161831736564636},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3542925715446472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32898128032684326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31284379959106445},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2634243369102478},{"id":"https://openalex.org/C35594927","wikidata":"https://www.wikidata.org/wiki/Q2265984","display_name":"Efficient estimator","level":4,"score":0.10023567080497742},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11222-009-9158-3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11222-009-9158-3","pdf_url":null,"source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmh:oai:publications.goettingen-research-online.de:2/5979","is_oa":true,"landing_page_url":"https://resolver.sub.uni-goettingen.de/purl?gro-2/5979","pdf_url":null,"source":{"id":"https://openalex.org/S4306401634","display_name":"GoeScholar  The Publication Server of the Georg-August-Universit\u00e4t G\u00f6ttingen (Georg-August-Universit\u00e4t G\u00f6ttingen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210122495","host_organization_name":"Asklepios Klinik St. Georg","host_organization_lineage":["https://openalex.org/I4210122495"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:publications.goettingen-research-online.de:2/5979","is_oa":true,"landing_page_url":"https://resolver.sub.uni-goettingen.de/purl?gro-2/5979","pdf_url":null,"source":{"id":"https://openalex.org/S4306401634","display_name":"GoeScholar  The Publication Server of the Georg-August-Universit\u00e4t G\u00f6ttingen (Georg-August-Universit\u00e4t G\u00f6ttingen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210122495","host_organization_name":"Asklepios Klinik St. Georg","host_organization_lineage":["https://openalex.org/I4210122495"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321870","display_name":"Georg-August-Universit\u00e4t G\u00f6ttingen","ror":"https://ror.org/01y9bpm73"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W15903490","https://openalex.org/W143236119","https://openalex.org/W158306839","https://openalex.org/W171292237","https://openalex.org/W214193251","https://openalex.org/W1423766661","https://openalex.org/W1486016120","https://openalex.org/W1520053542","https://openalex.org/W1529151133","https://openalex.org/W1535538352","https://openalex.org/W1567052132","https://openalex.org/W1570622790","https://openalex.org/W1862694079","https://openalex.org/W1874196095","https://openalex.org/W1965752946","https://openalex.org/W1969415786","https://openalex.org/W1969469580","https://openalex.org/W1970327181","https://openalex.org/W1971289666","https://openalex.org/W1971932180","https://openalex.org/W1976968384","https://openalex.org/W1982652137","https://openalex.org/W1990420052","https://openalex.org/W2004014822","https://openalex.org/W2006336297","https://openalex.org/W2007069447","https://openalex.org/W2012653948","https://openalex.org/W2016202972","https://openalex.org/W2019005118","https://openalex.org/W2020389170","https://openalex.org/W2038574031","https://openalex.org/W2052578052","https://openalex.org/W2053742224","https://openalex.org/W2057214799","https://openalex.org/W2058512798","https://openalex.org/W2061016774","https://openalex.org/W2062374872","https://openalex.org/W2070047497","https://openalex.org/W2074171296","https://openalex.org/W2074586297","https://openalex.org/W2074682976","https://openalex.org/W2087534654","https://openalex.org/W2095727687","https://openalex.org/W2102760656","https://openalex.org/W2119047368","https://openalex.org/W2122825543","https://openalex.org/W2129924796","https://openalex.org/W2130416410","https://openalex.org/W2134080536","https://openalex.org/W2135993243","https://openalex.org/W2144898279","https://openalex.org/W2149199519","https://openalex.org/W2152933101","https://openalex.org/W2166576847","https://openalex.org/W2166624680","https://openalex.org/W2185055605","https://openalex.org/W2334214145","https://openalex.org/W2492414201","https://openalex.org/W2581421583","https://openalex.org/W2602449753","https://openalex.org/W3008617006","https://openalex.org/W3101472415","https://openalex.org/W3124192614"],"related_works":["https://openalex.org/W4242964699","https://openalex.org/W2889116641","https://openalex.org/W624912034","https://openalex.org/W2057743791","https://openalex.org/W4302047046","https://openalex.org/W1796688137","https://openalex.org/W2086321337","https://openalex.org/W3121485895","https://openalex.org/W2752704183","https://openalex.org/W2083659801"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":7}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}