{"id":"https://openalex.org/W3216044898","doi":"https://doi.org/10.3390/e23121586","title":"Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator","display_name":"Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator","publication_year":2021,"publication_date":"2021-11-27","ids":{"openalex":"https://openalex.org/W3216044898","doi":"https://doi.org/10.3390/e23121586","mag":"3216044898","pmid":"https://pubmed.ncbi.nlm.nih.gov/34945891"},"language":"en","primary_location":{"id":"doi:10.3390/e23121586","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23121586","pdf_url":"https://www.mdpi.com/1099-4300/23/12/1586/pdf?version=1638507812","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/23/12/1586/pdf?version=1638507812","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083004617","display_name":"Dursun Ayd\u0131n","orcid":"https://orcid.org/0000-0001-8393-1270"},"institutions":[{"id":"https://openalex.org/I79946792","display_name":"Mu\u011fla University","ror":"https://ror.org/05n2cz176","country_code":"TR","type":"education","lineage":["https://openalex.org/I79946792"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Dursun Ayd\u0131n","raw_affiliation_strings":["Department of Statistics, Faculty of Science, Mugla Sitki Kocman University, Kotekli 48000, Turkey"],"raw_orcid":"https://orcid.org/0000-0001-8393-1270","affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Science, Mugla Sitki Kocman University, Kotekli 48000, Turkey","institution_ids":["https://openalex.org/I79946792"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039228742","display_name":"S. Ejaz Ahmed","orcid":"https://orcid.org/0000-0002-3873-8196"},"institutions":[{"id":"https://openalex.org/I186803428","display_name":"Brock University","ror":"https://ror.org/056am2717","country_code":"CA","type":"education","lineage":["https://openalex.org/I186803428"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Syed Ejaz Ahmed","raw_affiliation_strings":["Department of Mathematics and Statistics, Faculty of Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Faculty of Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1, Canada","institution_ids":["https://openalex.org/I186803428"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039626539","display_name":"Ersin Y\u0131lmaz","orcid":"https://orcid.org/0000-0002-9871-4700"},"institutions":[{"id":"https://openalex.org/I79946792","display_name":"Mu\u011fla University","ror":"https://ror.org/05n2cz176","country_code":"TR","type":"education","lineage":["https://openalex.org/I79946792"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Ersin Y\u0131lmaz","raw_affiliation_strings":["Department of Statistics, Faculty of Science, Mugla Sitki Kocman University, Kotekli 48000, Turkey"],"raw_orcid":"https://orcid.org/0000-0002-9871-4700","affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Science, Mugla Sitki Kocman University, Kotekli 48000, Turkey","institution_ids":["https://openalex.org/I79946792"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039626539"],"corresponding_institution_ids":["https://openalex.org/I79946792"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":1.2864,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82520013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"23","issue":"12","first_page":"1586","last_page":"1586"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9973000288009644,"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/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.8221747875213623},{"id":"https://openalex.org/keywords/spline","display_name":"Spline (mechanical)","score":0.760474681854248},{"id":"https://openalex.org/keywords/semiparametric-model","display_name":"Semiparametric model","score":0.5372740030288696},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.5359405279159546},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49646884202957153},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.487193763256073},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43291306495666504},{"id":"https://openalex.org/keywords/smoothing-spline","display_name":"Smoothing spline","score":0.425012469291687},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.42197537422180176},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4103720188140869},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36463239789009094},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3516380190849304},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29193389415740967},{"id":"https://openalex.org/keywords/spline-interpolation","display_name":"Spline interpolation","score":0.12191814184188843},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09126511216163635}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8221747875213623},{"id":"https://openalex.org/C10390562","wikidata":"https://www.wikidata.org/wiki/Q581809","display_name":"Spline (mechanical)","level":2,"score":0.760474681854248},{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.5372740030288696},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.5359405279159546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49646884202957153},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.487193763256073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43291306495666504},{"id":"https://openalex.org/C107457265","wikidata":"https://www.wikidata.org/wiki/Q7546460","display_name":"Smoothing spline","level":4,"score":0.425012469291687},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.42197537422180176},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4103720188140869},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36463239789009094},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3516380190849304},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29193389415740967},{"id":"https://openalex.org/C31447003","wikidata":"https://www.wikidata.org/wiki/Q545002","display_name":"Spline interpolation","level":3,"score":0.12191814184188843},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09126511216163635},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e23121586","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23121586","pdf_url":"https://www.mdpi.com/1099-4300/23/12/1586/pdf?version=1638507812","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:34945891","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34945891","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:5f52211745e1468990651bbd79b90c1a","is_oa":true,"landing_page_url":"https://doaj.org/article/5f52211745e1468990651bbd79b90c1a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 23, Iss 12, p 1586 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/23/12/1586/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e23121586","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 23; Issue 12; Pages: 1586","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8699840","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8699840","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e23121586","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23121586","pdf_url":"https://www.mdpi.com/1099-4300/23/12/1586/pdf?version=1638507812","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3216044898.pdf","grobid_xml":"https://content.openalex.org/works/W3216044898.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1423766661","https://openalex.org/W1967787804","https://openalex.org/W1968694834","https://openalex.org/W1984288612","https://openalex.org/W1986705681","https://openalex.org/W1990420052","https://openalex.org/W1996844063","https://openalex.org/W2027123933","https://openalex.org/W2031786162","https://openalex.org/W2041638842","https://openalex.org/W2042089645","https://openalex.org/W2045901075","https://openalex.org/W2049626087","https://openalex.org/W2058952802","https://openalex.org/W2065540158","https://openalex.org/W2079775628","https://openalex.org/W2083374842","https://openalex.org/W2105168783","https://openalex.org/W2109785413","https://openalex.org/W2131057697","https://openalex.org/W2162870748","https://openalex.org/W2168489635","https://openalex.org/W2222886592","https://openalex.org/W2270311753","https://openalex.org/W2613786734","https://openalex.org/W2791682276","https://openalex.org/W2890835987","https://openalex.org/W3036633953","https://openalex.org/W3044165957","https://openalex.org/W3122347686","https://openalex.org/W3185937767","https://openalex.org/W4206419526","https://openalex.org/W4241079352","https://openalex.org/W4293241248"],"related_works":["https://openalex.org/W2462869830","https://openalex.org/W1991430094","https://openalex.org/W2625865326","https://openalex.org/W2085166207","https://openalex.org/W1564806038","https://openalex.org/W3150947797","https://openalex.org/W3137444672","https://openalex.org/W2365211194","https://openalex.org/W1970492091","https://openalex.org/W4312299628"],"abstract_inverted_index":{"This":[0],"paper":[1],"focuses":[2],"on":[3,65,115],"the":[4,10,47,50,60,66,72,79,87,100,103,116,130,137,149,152,174,177],"adaptive":[5],"spline":[6],"(A-spline)":[7],"fitting":[8],"of":[9,49,78,102,151,176],"semiparametric":[11,51,112,138],"regression":[12],"model":[13],"to":[14,29,99,119,128,147,172,181],"time":[15],"series":[16],"data":[17,39,62,74,121,167],"with":[18,37,123],"right-censored":[19,85],"observations.":[20],"Typically,":[21],"there":[22],"are":[23],"two":[24],"main":[25],"problems":[26],"that":[27],"need":[28],"be":[30],"solved":[31,58],"in":[32],"such":[33],"a":[34,42,110,144,158,165,183],"case:":[35],"dealing":[36],"censored":[38,96],"and":[40,127,164,180],"obtaining":[41],"proper":[43],"A-spline":[44,117,153],"estimator":[45,113,140,179],"for":[46,84,94],"components":[48],"model.":[52],"The":[53],"first":[54],"problem":[55,132],"is":[56,76,91],"traditionally":[57],"by":[59],"synthetic":[61,73],"approach":[63,118],"based":[64,114],"Kaplan-Meier":[67],"estimator.":[68,154],"In":[69,105,135],"practice,":[70],"although":[71],"technique":[75],"one":[77],"most":[80],"widely":[81],"used":[82,142],"solutions":[83],"observations,":[86],"transformed":[88],"data's":[89],"structure":[90],"distorted,":[92],"especially":[93],"heavily":[95],"datasets,":[97],"due":[98],"nature":[101],"approach.":[104],"this":[106,156],"paper,":[107],"we":[108],"introduced":[109],"modified":[111],"overcome":[120],"irregularity":[122],"minimum":[124],"information":[125],"loss":[126],"resolve":[129],"second":[131],"described":[133],"above.":[134],"addition,":[136],"B-spline":[139],"was":[141],"as":[143],"benchmark":[145],"method":[146],"gauge":[148],"success":[150],"To":[155],"end,":[157],"detailed":[159],"Monte":[160],"Carlo":[161],"simulation":[162],"study":[163],"real":[166],"sample":[168],"were":[169],"carried":[170],"out":[171],"evaluate":[173],"performance":[175],"proposed":[178],"make":[182],"practical":[184],"comparison.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}