{"id":"https://openalex.org/W4395012628","doi":"https://doi.org/10.1080/10618600.2024.2330517","title":"Group Selection and Shrinkage: Structured Sparsity for Semiparametric Additive Models","display_name":"Group Selection and Shrinkage: Structured Sparsity for Semiparametric Additive Models","publication_year":2024,"publication_date":"2024-04-22","ids":{"openalex":"https://openalex.org/W4395012628","doi":"https://doi.org/10.1080/10618600.2024.2330517"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2330517","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2330517","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2330517?download=true","source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2330517?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076142233","display_name":"Ryan Thompson","orcid":"https://orcid.org/0000-0003-3612-9749"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I4210101388","display_name":"Health Sciences and Nutrition","ror":"https://ror.org/0152bt112","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4210101388","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Ryan Thompson","raw_affiliation_strings":["Data61, Commonwealth Scientific and Industrial Research Organisation","Department of Econometrics and Business Statistics, Monash University","School of Mathematics and Statistics, University of New South Wales","School of Mathematics and Statistics, University of New South Wales, Sydney, Australia","Data61, Commonwealth Scientific and Industrial Research Organisation, Sydney, Australia","Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Data61, Commonwealth Scientific and Industrial Research Organisation","institution_ids":["https://openalex.org/I4210101388","https://openalex.org/I1292875679","https://openalex.org/I42894916"]},{"raw_affiliation_string":"Department of Econometrics and Business Statistics, Monash University","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"School of Mathematics and Statistics, University of New South Wales","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Mathematics and Statistics, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"Data61, Commonwealth Scientific and Industrial Research Organisation, Sydney, Australia","institution_ids":["https://openalex.org/I1292875679","https://openalex.org/I42894916"]},{"raw_affiliation_string":"Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027718962","display_name":"Farshid Vahid","orcid":null},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Farshid Vahid","raw_affiliation_strings":["Department of Econometrics and Business Statistics, Monash University","Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Econometrics and Business Statistics, Monash University","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076142233"],"corresponding_institution_ids":["https://openalex.org/I1292875679","https://openalex.org/I31746571","https://openalex.org/I4210101388","https://openalex.org/I42894916","https://openalex.org/I56590836"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05673234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"4","first_page":"1286","last_page":"1297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9897000193595886,"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":0.9894000291824341,"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/shrinkage","display_name":"Shrinkage","score":0.7099640369415283},{"id":"https://openalex.org/keywords/semiparametric-model","display_name":"Semiparametric model","score":0.6504310369491577},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.591720461845398},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.5579911470413208},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.5056366920471191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4880906343460083},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4615829586982727},{"id":"https://openalex.org/keywords/group-selection","display_name":"Group selection","score":0.45318955183029175},{"id":"https://openalex.org/keywords/r-package","display_name":"R package","score":0.44454053044319153},{"id":"https://openalex.org/keywords/additive-model","display_name":"Additive model","score":0.41965004801750183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3842526078224182},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3824254274368286},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3320556879043579},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3257356286048889},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.19759395718574524}],"concepts":[{"id":"https://openalex.org/C180145272","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage","level":2,"score":0.7099640369415283},{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.6504310369491577},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.591720461845398},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.5579911470413208},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.5056366920471191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4880906343460083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4615829586982727},{"id":"https://openalex.org/C51520907","wikidata":"https://www.wikidata.org/wiki/Q874437","display_name":"Group selection","level":3,"score":0.45318955183029175},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.44454053044319153},{"id":"https://openalex.org/C203223496","wikidata":"https://www.wikidata.org/wiki/Q4681344","display_name":"Additive model","level":2,"score":0.41965004801750183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3842526078224182},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3824254274368286},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3320556879043579},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3257356286048889},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.19759395718574524},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/10618600.2024.2330517","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2330517","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2330517?download=true","source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:monash.edu:publications/67d50e8d-ea3c-45a8-b10c-49976e408936","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/67d50e8d-ea3c-45a8-b10c-49976e408936","pdf_url":"https://researchmgt.monash.edu/ws/files/685283332/589911258-oa.pdf","source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Thompson, R & Vahid, F 2024, 'Group selection and shrinkage : structured sparsity for semiparametric additive models', Journal of Computational and Graphical Statistics, vol. 33, no. 4, pp. 1286-1297. https://doi.org/10.1080/10618600.2024.2330517","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/10618600.2024.2330517","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2330517","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2330517?download=true","source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5799999833106995,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4395012628.pdf","grobid_xml":"https://content.openalex.org/works/W4395012628.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1540764732","https://openalex.org/W1902601042","https://openalex.org/W1962147060","https://openalex.org/W1965125844","https://openalex.org/W1970554427","https://openalex.org/W1981657694","https://openalex.org/W2023901033","https://openalex.org/W2065343359","https://openalex.org/W2066512999","https://openalex.org/W2073738917","https://openalex.org/W2074682976","https://openalex.org/W2082562176","https://openalex.org/W2083346837","https://openalex.org/W2101432452","https://openalex.org/W2106398669","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2153841684","https://openalex.org/W2159700154","https://openalex.org/W2199135087","https://openalex.org/W2239386085","https://openalex.org/W2257263437","https://openalex.org/W2323665732","https://openalex.org/W2593996946","https://openalex.org/W2744157898","https://openalex.org/W2963242773","https://openalex.org/W2999243450","https://openalex.org/W3048822613","https://openalex.org/W3098306969","https://openalex.org/W3121553976","https://openalex.org/W3122008423","https://openalex.org/W3122503089","https://openalex.org/W3153278865","https://openalex.org/W3183109983","https://openalex.org/W3194521138","https://openalex.org/W4210643453","https://openalex.org/W4235256446","https://openalex.org/W4287903375","https://openalex.org/W4311626684"],"related_works":["https://openalex.org/W2005928212","https://openalex.org/W4312140143","https://openalex.org/W1025582088","https://openalex.org/W2951978129","https://openalex.org/W1981276144","https://openalex.org/W2039581707","https://openalex.org/W1540524887","https://openalex.org/W2044180931","https://openalex.org/W2077160926","https://openalex.org/W2149420770"],"abstract_inverted_index":{"Sparse":[0],"regression":[1,72],"and":[2,16,63,123,147],"classification":[3],"estimators":[4,34,46,103],"that":[5,35,86],"respect":[6],"group":[7,37],"structures":[8],"have":[9],"application":[10,75],"to":[11,23,27,93,112],"an":[12,54,74,141],"assortment":[13],"of":[14,70,90,151],"statistical":[15],"machine":[17],"learning":[18,22],"problems,":[19],"from":[20],"multitask":[21],"sparse":[24,33,80,131],"additive":[25,82,133],"modeling":[26,119],"hierarchical":[28],"selection.This":[29],"work":[30],"introduces":[31],"structured":[32],"combine":[36],"subset":[38],"selection":[39],"with":[40],"shrinkage.To":[41],"accommodate":[42],"sophisticated":[43],"structures,":[44],"our":[45,152],"allow":[47],"for":[48,57,68],"arbitrary":[49],"overlap":[50],"between":[51,144],"groups.We":[52],"develop":[53],"optimization":[55],"framework":[56],"fitting":[58],"the":[59,71,88,101,137,158],"nonconvex":[60],"regularization":[61],"surface":[62],"present":[64],"finite-sample":[65],"error":[66],"bounds":[67],"estimation":[69],"function.As":[73],"requiring":[76],"structure,":[77],"we":[78,114],"study":[79],"semiparametric":[81,132],"modeling,":[83],"a":[84],"procedure":[85],"allows":[87],"effect":[89],"each":[91],"predictor":[92],"be":[94],"zero,":[95],"linear,":[96],"or":[97],"nonlinear.For":[98],"this":[99],"task,":[100],"new":[102,138],"improve":[104],"across":[105],"several":[106],"metrics":[107],"on":[108],"synthetic":[109],"data":[110],"compared":[111],"alternatives.Finally,":[113],"demonstrate":[115],"their":[116],"efficacy":[117],"in":[118,157],"supermarket":[120],"foot":[121],"traffic":[122],"economic":[124],"recessions":[125],"using":[126,136],"many":[127],"predictors.These":[128],"demonstrations":[129],"suggest":[130],"models,":[134],"fit":[135],"estimators,":[139],"are":[140,154],"excellent":[142],"compromise":[143],"fully":[145,148],"linear":[146],"nonparametric":[149],"alternatives.All":[150],"algorithms":[153],"made":[155],"available":[156],"scalable":[159],"implementation":[160],"grpsel.":[161]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}