{"id":"https://openalex.org/W4414493795","doi":"https://doi.org/10.1007/s11222-025-10734-3","title":"Adaptive Generalized P-Splines for Functional Data: A Statistical Framework via Blockwise GSVD","display_name":"Adaptive Generalized P-Splines for Functional Data: A Statistical Framework via Blockwise GSVD","publication_year":2025,"publication_date":"2025-09-25","ids":{"openalex":"https://openalex.org/W4414493795","doi":"https://doi.org/10.1007/s11222-025-10734-3"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-025-10734-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-025-10734-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-025-10734-3.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-025-10734-3.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072353341","display_name":"Anna De Magistris","orcid":"https://orcid.org/0009-0004-1633-2365"},"institutions":[{"id":"https://openalex.org/I197809005","display_name":"University of Campania \"Luigi Vanvitelli\"","ror":"https://ror.org/02kqnpp86","country_code":"IT","type":"education","lineage":["https://openalex.org/I197809005"]},{"id":"https://openalex.org/I4210126337","display_name":"University of Campania \"Luigi Vanvitelli\"","ror":null,"country_code":"IT","type":null,"lineage":["https://openalex.org/I4210126337"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Anna De Magistris","raw_affiliation_strings":["Department of Mathematics and Physics, University of Campania \u201cLuigi Vanvitelli\u201d, Viale Lincoln, 5, 81100, Caserta, Italy","Department of Mathematics and Physics, University of Campania \"Luigi Vanvitelli\", Viale Lincoln, 5, 81100, Caserta, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Physics, University of Campania \u201cLuigi Vanvitelli\u201d, Viale Lincoln, 5, 81100, Caserta, Italy","institution_ids":["https://openalex.org/I4210126337"]},{"raw_affiliation_string":"Department of Mathematics and Physics, University of Campania \"Luigi Vanvitelli\", Viale Lincoln, 5, 81100, Caserta, Italy","institution_ids":["https://openalex.org/I197809005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089561475","display_name":"Elvira Romano","orcid":"https://orcid.org/0000-0001-8998-7099"},"institutions":[{"id":"https://openalex.org/I197809005","display_name":"University of Campania \"Luigi Vanvitelli\"","ror":"https://ror.org/02kqnpp86","country_code":"IT","type":"education","lineage":["https://openalex.org/I197809005"]},{"id":"https://openalex.org/I4210126337","display_name":"University of Campania \"Luigi Vanvitelli\"","ror":null,"country_code":"IT","type":null,"lineage":["https://openalex.org/I4210126337"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Elvira Romano","raw_affiliation_strings":["Department of Mathematics and Physics, University of Campania \u201cLuigi Vanvitelli\u201d, Viale Lincoln, 5, 81100, Caserta, Italy","Department of Mathematics and Physics, University of Campania \"Luigi Vanvitelli\", Viale Lincoln, 5, 81100, Caserta, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Physics, University of Campania \u201cLuigi Vanvitelli\u201d, Viale Lincoln, 5, 81100, Caserta, Italy","institution_ids":["https://openalex.org/I4210126337"]},{"raw_affiliation_string":"Department of Mathematics and Physics, University of Campania \"Luigi Vanvitelli\", Viale Lincoln, 5, 81100, Caserta, Italy","institution_ids":["https://openalex.org/I197809005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076486170","display_name":"Rosanna Campagna","orcid":"https://orcid.org/0000-0003-4694-0113"},"institutions":[{"id":"https://openalex.org/I197809005","display_name":"University of Campania \"Luigi Vanvitelli\"","ror":"https://ror.org/02kqnpp86","country_code":"IT","type":"education","lineage":["https://openalex.org/I197809005"]},{"id":"https://openalex.org/I4210126337","display_name":"University of Campania \"Luigi Vanvitelli\"","ror":null,"country_code":"IT","type":null,"lineage":["https://openalex.org/I4210126337"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Rosanna Campagna","raw_affiliation_strings":["Department of Mathematics and Physics, University of Campania \u201cLuigi Vanvitelli\u201d, Viale Lincoln, 5, 81100, Caserta, Italy","Department of Mathematics and Physics, University of Campania \"Luigi Vanvitelli\", Viale Lincoln, 5, 81100, Caserta, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Physics, University of Campania \u201cLuigi Vanvitelli\u201d, Viale Lincoln, 5, 81100, Caserta, Italy","institution_ids":["https://openalex.org/I4210126337"]},{"raw_affiliation_string":"Department of Mathematics and Physics, University of Campania \"Luigi Vanvitelli\", Viale Lincoln, 5, 81100, Caserta, Italy","institution_ids":["https://openalex.org/I197809005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072353341"],"corresponding_institution_ids":["https://openalex.org/I197809005","https://openalex.org/I4210126337"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25092101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":"6","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.984499990940094,"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/tikhonov-regularization","display_name":"Tikhonov regularization","score":0.7512999773025513},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.7337999939918518},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6014999747276306},{"id":"https://openalex.org/keywords/compact-space","display_name":"Compact space","score":0.5759999752044678},{"id":"https://openalex.org/keywords/spline","display_name":"Spline (mechanical)","score":0.4805000126361847},{"id":"https://openalex.org/keywords/smoothing-spline","display_name":"Smoothing spline","score":0.43050000071525574},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.4203000068664551},{"id":"https://openalex.org/keywords/approximation-theory","display_name":"Approximation theory","score":0.3702000081539154}],"concepts":[{"id":"https://openalex.org/C152442038","wikidata":"https://www.wikidata.org/wiki/Q2778212","display_name":"Tikhonov regularization","level":3,"score":0.7512999773025513},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7337999939918518},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6014999747276306},{"id":"https://openalex.org/C18648836","wikidata":"https://www.wikidata.org/wiki/Q381892","display_name":"Compact space","level":2,"score":0.5759999752044678},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5188999772071838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5108000040054321},{"id":"https://openalex.org/C10390562","wikidata":"https://www.wikidata.org/wiki/Q581809","display_name":"Spline (mechanical)","level":2,"score":0.4805000126361847},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4763999879360199},{"id":"https://openalex.org/C107457265","wikidata":"https://www.wikidata.org/wiki/Q7546460","display_name":"Smoothing spline","level":4,"score":0.43050000071525574},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41830000281333923},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38940000534057617},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3644999861717224},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.310699999332428},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C2779863119","wikidata":"https://www.wikidata.org/wiki/Q6423048","display_name":"Knot (papermaking)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C15945459","wikidata":"https://www.wikidata.org/wiki/Q2083109","display_name":"B-spline","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C51820054","wikidata":"https://www.wikidata.org/wiki/Q5508814","display_name":"Functional data analysis","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11222-025-10734-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-025-10734-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-025-10734-3.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11222-025-10734-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-025-10734-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-025-10734-3.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1145458839","display_name":null,"funder_award_id":"PRIN 2022","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G1857088242","display_name":null,"funder_award_id":"Mission 4","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2816804289","display_name":null,"funder_award_id":"Resilience Plan (NRRP)","funder_id":"https://openalex.org/F4320321873","funder_display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca"},{"id":"https://openalex.org/G2974696270","display_name":null,"funder_award_id":"Component 2","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G3613825015","display_name":"Biomimetic process design for tissue regeneration: \nfrom bench to bedside via in silico modelling","funder_award_id":"279100","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4570350399","display_name":"Towards Open Societies? Trends, Variations and Driving Forces of Intergenerational Social Mobility in Europe over the Past Three Centuries","funder_award_id":"230279","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G490430286","display_name":null,"funder_award_id":"PRIN 2022","funder_id":"https://openalex.org/F4320321873","funder_display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca"},{"id":"https://openalex.org/G5245466801","display_name":null,"funder_award_id":"PRIN 2022","funder_id":"https://openalex.org/F4320311030","funder_display_name":"Istituto Nazionale di Alta Matematica \"Francesco Severi\""},{"id":"https://openalex.org/G7066850978","display_name":null,"funder_award_id":"Research (MUR)","funder_id":"https://openalex.org/F4320321873","funder_display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca"},{"id":"https://openalex.org/G8051717526","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8386731437","display_name":null,"funder_award_id":"Resilience Plan (NRRP)","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320311030","display_name":"Istituto Nazionale di Alta Matematica \"Francesco Severi\"","ror":"https://ror.org/01vx64p53"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321873","display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca","ror":"https://ror.org/0166hxq48"},{"id":"https://openalex.org/F4320325777","display_name":"Universit\u00e0 degli Studi della Campania Luigi Vanvitelli","ror":null},{"id":"https://openalex.org/F4320334079","display_name":"Gruppo Nazionale per il Calcolo Scientifico","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414493795.pdf","grobid_xml":"https://content.openalex.org/works/W4414493795.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1538934584","https://openalex.org/W1594234351","https://openalex.org/W1924592273","https://openalex.org/W1993245243","https://openalex.org/W2017904507","https://openalex.org/W2019967922","https://openalex.org/W2048037529","https://openalex.org/W2055970573","https://openalex.org/W2065730960","https://openalex.org/W2067596735","https://openalex.org/W2105428650","https://openalex.org/W2121203842","https://openalex.org/W2128860595","https://openalex.org/W2162870748","https://openalex.org/W2487770199","https://openalex.org/W2996370717","https://openalex.org/W3211353578","https://openalex.org/W4292156489","https://openalex.org/W4385217329","https://openalex.org/W4400480225"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"In":[1],"this":[2],"work,":[3],"we":[4,58],"introduce":[5],"a":[6,33,60],"novel":[7],"approach":[8,105],"for":[9,36],"functional":[10,84],"data":[11],"approximation":[12,74,118],"based":[13],"on":[14,96],"generalized":[15],"P-splines":[16],"with":[17],"non-uniform":[18],"and":[19,41,90,99,111,120],"adaptively":[20],"placed":[21],"knots.":[22],"The":[23,72],"key":[24],"innovation":[25],"of":[26,32,43,117],"our":[27,104],"proposal":[28],"is":[29],"the":[30,39,44,49,54,79,82],"integration":[31],"conditioning-aware":[34],"strategy":[35],"selecting":[37],"both":[38,97],"number":[40],"positions":[42],"knots,":[45],"as":[46,48],"well":[47],"regularization":[50,56],"parameters.":[51],"By":[52],"reformulating":[53],"Tikhonov":[55],"problem,":[57],"propose":[59],"computationally":[61],"efficient":[62],"criterion":[63],"that":[64,103],"controls":[65],"model":[66],"complexity":[67],"while":[68],"ensuring":[69],"numerical":[70,93],"stability.":[71],"resulting":[73],"framework":[75],"not":[76],"only":[77],"improves":[78],"fit":[80],"across":[81],"entire":[83],"domain":[85],"but":[86],"also":[87],"maintains":[88],"compactness":[89],"robustness.":[91],"Extensive":[92],"experiments":[94],"conducted":[95],"synthetic":[98],"real-world":[100],"datasets":[101],"demonstrate":[102],"significantly":[106],"outperforms":[107],"traditional":[108],"free":[109],"knot":[110],"smoothing":[112],"spline":[113],"methods":[114],"in":[115],"terms":[116],"error":[119],"conditioning.":[121]},"counts_by_year":[],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}
