{"id":"https://openalex.org/W7118689975","doi":"https://doi.org/10.1007/s11222-025-10812-6","title":"The Group R2D2 Shrinkage Prior for Sparse Linear Models with Grouped Covariates","display_name":"The Group R2D2 Shrinkage Prior for Sparse Linear Models with Grouped Covariates","publication_year":2026,"publication_date":"2026-01-06","ids":{"openalex":"https://openalex.org/W7118689975","doi":"https://doi.org/10.1007/s11222-025-10812-6"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-025-10812-6","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11222-025-10812-6","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006784072","display_name":"Eric Yanchenko","orcid":"https://orcid.org/0000-0001-6075-6449"},"institutions":[{"id":"https://openalex.org/I70999451","display_name":"Akita International University","ror":"https://ror.org/05qz4zw08","country_code":"JP","type":"education","lineage":["https://openalex.org/I70999451"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Eric Yanchenko","raw_affiliation_strings":["Human and AI Center, Akita International University, Akita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Human and AI Center, Akita International University, Akita, Japan","institution_ids":["https://openalex.org/I70999451"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076831167","display_name":"Kaoru Irie","orcid":null},"institutions":[{"id":"https://openalex.org/I3132069261","display_name":"Japan University of Economics","ror":"https://ror.org/039k5fe46","country_code":"JP","type":"education","lineage":["https://openalex.org/I3132069261"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kaoru Irie","raw_affiliation_strings":["Faculty of Economics, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Economics, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I3132069261","https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054166002","display_name":"Shonosuke Sugasawa","orcid":"https://orcid.org/0000-0002-9495-4280"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shonosuke Sugasawa","raw_affiliation_strings":["Faculty of Economics, Keio University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Economics, Keio University, Tokyo, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5006784072"],"corresponding_institution_ids":["https://openalex.org/I70999451"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04589666,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.5669999718666077,"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":0.5669999718666077,"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":0.25119999051094055,"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":0.06499999761581421,"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":0.9223999977111816},{"id":"https://openalex.org/keywords/shrinkage","display_name":"Shrinkage","score":0.838100016117096},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.7382000088691711},{"id":"https://openalex.org/keywords/shrinkage-estimator","display_name":"Shrinkage estimator","score":0.6449000239372253},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.633400022983551},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.6154000163078308},{"id":"https://openalex.org/keywords/dirichlet-process","display_name":"Dirichlet process","score":0.4722999930381775},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.4553000032901764},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.454800009727478},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.45339998602867126}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.9223999977111816},{"id":"https://openalex.org/C180145272","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage","level":2,"score":0.838100016117096},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.7382000088691711},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6471999883651733},{"id":"https://openalex.org/C102592046","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage estimator","level":5,"score":0.6449000239372253},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.633400022983551},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.6154000163078308},{"id":"https://openalex.org/C2781280628","wikidata":"https://www.wikidata.org/wiki/Q5280766","display_name":"Dirichlet process","level":3,"score":0.4722999930381775},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4553000032901764},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.454800009727478},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.45339998602867126},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42640000581741333},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3790000081062317},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3264999985694885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32350000739097595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31540000438690186},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.30720001459121704},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.2847999930381775},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.27649998664855957},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.2513999938964844},{"id":"https://openalex.org/C74127309","wikidata":"https://www.wikidata.org/wiki/Q3455886","display_name":"Nonparametric regression","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11222-025-10812-6","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11222-025-10812-6","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2905133878","display_name":null,"funder_award_id":"20H00080, 21H00699, 24K00244, 24K00175, 24K21420 and 24K22613","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W45374770","https://openalex.org/W1971421925","https://openalex.org/W1976365540","https://openalex.org/W1982652137","https://openalex.org/W1998966727","https://openalex.org/W1999894343","https://openalex.org/W2061820396","https://openalex.org/W2082633919","https://openalex.org/W2110589526","https://openalex.org/W2127048411","https://openalex.org/W2135046866","https://openalex.org/W2145768101","https://openalex.org/W2150149003","https://openalex.org/W2559571361","https://openalex.org/W2792990871","https://openalex.org/W2963047405","https://openalex.org/W2972298634","https://openalex.org/W3088522645","https://openalex.org/W3217742050","https://openalex.org/W4221061518","https://openalex.org/W4382724518","https://openalex.org/W4386515913","https://openalex.org/W4387975053","https://openalex.org/W4410191118","https://openalex.org/W4410438608","https://openalex.org/W4411297983"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2026-01-08T00:00:00"}