{"id":"https://openalex.org/W2055341260","doi":"https://doi.org/10.1142/s0219691309002969","title":"ON WAVELET METHODS FOR TESTING EQUALITY OF MEAN RESPONSE CURVES","display_name":"ON WAVELET METHODS FOR TESTING EQUALITY OF MEAN RESPONSE CURVES","publication_year":2009,"publication_date":"2009-05-01","ids":{"openalex":"https://openalex.org/W2055341260","doi":"https://doi.org/10.1142/s0219691309002969","mag":"2055341260"},"language":"en","primary_location":{"id":"doi:10.1142/s0219691309002969","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691309002969","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","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/A5058782332","display_name":"Pengfei Guo","orcid":"https://orcid.org/0000-0001-6976-7179"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"PENGFEI GUO","raw_affiliation_strings":["Department of Mathematics and Statistics, York University, Toronto, ON, Canada, M3J 1P3, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, York University, Toronto, ON, Canada, M3J 1P3, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082433582","display_name":"Alwell J. Oyet","orcid":"https://orcid.org/0000-0003-0752-6112"},"institutions":[{"id":"https://openalex.org/I130438778","display_name":"Memorial University of Newfoundland","ror":"https://ror.org/04haebc03","country_code":"CA","type":"education","lineage":["https://openalex.org/I130438778"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"ALWELL JULIUS OYET","raw_affiliation_strings":["Department of Mathematics and Statistics, Memorial University, St. John's, NL, A1C 5S7, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Memorial University, St. John's, NL, A1C 5S7, Canada","institution_ids":["https://openalex.org/I130438778"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9699,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.77303396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"07","issue":"03","first_page":"357","last_page":"373"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9973000288009644,"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":0.9973000288009644,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"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/wavelet","display_name":"Wavelet","score":0.9105837345123291},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5956172943115234},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5886702537536621},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5785337686538696},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.490100234746933},{"id":"https://openalex.org/keywords/cascade-algorithm","display_name":"Cascade algorithm","score":0.4677935242652893},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4440220296382904},{"id":"https://openalex.org/keywords/orthogonal-wavelet","display_name":"Orthogonal wavelet","score":0.43886223435401917},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.4310305118560791},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4284886419773102},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.4241233766078949},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.38495415449142456},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37393030524253845},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3278975784778595},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.3209187984466553},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29630935192108154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2615104913711548},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1409619152545929},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06497898697853088}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.9105837345123291},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5956172943115234},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5886702537536621},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5785337686538696},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.490100234746933},{"id":"https://openalex.org/C88829872","wikidata":"https://www.wikidata.org/wiki/Q5048176","display_name":"Cascade algorithm","level":5,"score":0.4677935242652893},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4440220296382904},{"id":"https://openalex.org/C2777451244","wikidata":"https://www.wikidata.org/wiki/Q3352512","display_name":"Orthogonal wavelet","level":5,"score":0.43886223435401917},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.4310305118560791},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4284886419773102},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.4241233766078949},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38495415449142456},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37393030524253845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3278975784778595},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.3209187984466553},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29630935192108154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2615104913711548},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1409619152545929},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06497898697853088},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219691309002969","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691309002969","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1984195280","https://openalex.org/W1991418299","https://openalex.org/W1995152313","https://openalex.org/W1995696383","https://openalex.org/W1997624340","https://openalex.org/W2019038469","https://openalex.org/W2022461842","https://openalex.org/W2030934791","https://openalex.org/W2067059611","https://openalex.org/W2068903499","https://openalex.org/W2070855110","https://openalex.org/W2071057645","https://openalex.org/W2075187577","https://openalex.org/W2075997966","https://openalex.org/W2080558403","https://openalex.org/W2098175429","https://openalex.org/W2100977513","https://openalex.org/W2110065044","https://openalex.org/W2118724100","https://openalex.org/W2318511587","https://openalex.org/W2468543752","https://openalex.org/W4255272544"],"related_works":["https://openalex.org/W2086760654","https://openalex.org/W2085792030","https://openalex.org/W1889651196","https://openalex.org/W2059234650","https://openalex.org/W2101997086","https://openalex.org/W1551148373","https://openalex.org/W2368320199","https://openalex.org/W2471144219","https://openalex.org/W29983228","https://openalex.org/W2054813816"],"abstract_inverted_index":{"In":[0],"this":[1,82],"article,":[2],"we":[3],"exploit":[4],"the":[5,16,33,49,52,55,58,61,65,85,106,131],"adaptive":[6],"properties":[7],"of":[8,18,39,48,54,60,105,135],"wavelets":[9],"to":[10,31,64,112,121],"develop":[11],"some":[12,113],"procedures":[13],"for":[14,127],"testing":[15,86],"equality":[17],"nonlinear":[19],"and":[20,102,110],"nonparametric":[21],"mean":[22],"response":[23,125],"curves":[24,126],"which":[25],"are":[26,108,118],"assumed":[27],"by":[28],"an":[29,69],"experimenter":[30],"be":[32],"underlying":[34],"functions":[35],"generating":[36],"several":[37],"groups":[38],"data":[40,122],"with":[41],"possibly":[42],"hetereoscedastic":[43],"errors.":[44],"The":[45,100,116],"essential":[46],"feature":[47],"techniques":[50],"is":[51],"transformation":[53,73],"problem":[56,87,93],"from":[57],"domain":[59,67],"input":[62],"variable":[63],"wavelet":[66,72,91,97],"through":[68],"orthogonal":[70],"discrete":[71],"or":[74,94,133],"a":[75,90,95,136],"multiresolution":[76],"expansion.":[77],"We":[78],"shall":[79],"see":[80],"that":[81],"greatly":[83],"simplifies":[84],"into":[88],"either":[89],"thresholding":[92],"linear":[96],"regression":[98],"problem.":[99],"size":[101],"power":[103],"performances":[104],"tests":[107,117],"reported":[109],"compared":[111],"existing":[114],"methods.":[115],"also":[119],"applied":[120],"on":[123],"dose":[124],"vascular":[128],"relaxation":[129],"in":[130],"absence":[132],"presence":[134],"nitric":[137],"oxide":[138],"inhibitor.":[139]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}