{"id":"https://openalex.org/W2080517174","doi":"https://doi.org/10.1080/03610910802050902","title":"Undercoverage of Wavelet-Based Resampling Confidence Intervals","display_name":"Undercoverage of Wavelet-Based Resampling Confidence Intervals","publication_year":2008,"publication_date":"2008-08-01","ids":{"openalex":"https://openalex.org/W2080517174","doi":"https://doi.org/10.1080/03610910802050902","mag":"2080517174"},"language":"en","primary_location":{"id":"doi:10.1080/03610910802050902","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802050902","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","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/A5027778319","display_name":"Liansheng Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Liansheng Tang","raw_affiliation_strings":["George Mason University","Department of Statistics, George Mason University, Fairfax, Virginia - USA"],"affiliations":[{"raw_affiliation_string":"George Mason University","institution_ids":["https://openalex.org/I162714631"]},{"raw_affiliation_string":"Department of Statistics, George Mason University, Fairfax, Virginia - USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103509010","display_name":"Wayne A. Woodward","orcid":null},"institutions":[{"id":"https://openalex.org/I178169726","display_name":"Southern Methodist University","ror":"https://ror.org/042tdr378","country_code":"US","type":"education","lineage":["https://openalex.org/I178169726"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wayne A. Woodward","raw_affiliation_strings":["Southern Methodist University","Department of Statistics , Southern Methodist University , Dallas, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Southern Methodist University","institution_ids":["https://openalex.org/I178169726"]},{"raw_affiliation_string":"Department of Statistics , Southern Methodist University , Dallas, Texas, USA","institution_ids":["https://openalex.org/I178169726"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033847414","display_name":"William R. Schucany","orcid":null},"institutions":[{"id":"https://openalex.org/I178169726","display_name":"Southern Methodist University","ror":"https://ror.org/042tdr378","country_code":"US","type":"education","lineage":["https://openalex.org/I178169726"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William R. Schucany","raw_affiliation_strings":["Southern Methodist University","Department of Statistics , Southern Methodist University , Dallas, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Southern Methodist University","institution_ids":["https://openalex.org/I178169726"]},{"raw_affiliation_string":"Department of Statistics , Southern Methodist University , Dallas, Texas, USA","institution_ids":["https://openalex.org/I178169726"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027778319"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.3568,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.64105663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"37","issue":"7","first_page":"1307","last_page":"1315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9947999715805054,"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":0.9947999715805054,"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/T13487","display_name":"Statistical and numerical algorithms","score":0.9930999875068665,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9890999794006348,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.8065645694732666},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6287502646446228},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5517954230308533},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5288565754890442},{"id":"https://openalex.org/keywords/permutation","display_name":"Permutation (music)","score":0.4582464098930359},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.43319591879844666},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4162098169326782},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4055441617965698},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3900510370731354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36221715807914734},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3385162353515625}],"concepts":[{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.8065645694732666},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6287502646446228},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5517954230308533},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5288565754890442},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.4582464098930359},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.43319591879844666},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4162098169326782},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4055441617965698},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3900510370731354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36221715807914734},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3385162353515625},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910802050902","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802050902","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W654435104","https://openalex.org/W1582484699","https://openalex.org/W1582705120","https://openalex.org/W1975978539","https://openalex.org/W1980149518","https://openalex.org/W1995945562","https://openalex.org/W2001541996","https://openalex.org/W2035843433","https://openalex.org/W2043526380","https://openalex.org/W2050955927","https://openalex.org/W2062962812","https://openalex.org/W2072647566","https://openalex.org/W2093272448","https://openalex.org/W2094243598","https://openalex.org/W2097879961","https://openalex.org/W2099566014","https://openalex.org/W2121493559","https://openalex.org/W2132984323","https://openalex.org/W2146842127","https://openalex.org/W2156899486","https://openalex.org/W2158940042","https://openalex.org/W2485347808","https://openalex.org/W2971268466","https://openalex.org/W3106889297","https://openalex.org/W4250507776","https://openalex.org/W4298352105","https://openalex.org/W4298872162"],"related_works":["https://openalex.org/W2021333301","https://openalex.org/W2077508419","https://openalex.org/W2006114390","https://openalex.org/W2380800094","https://openalex.org/W2056203905","https://openalex.org/W4385400511","https://openalex.org/W2162206208","https://openalex.org/W2023660371","https://openalex.org/W2507906577","https://openalex.org/W3090113802"],"abstract_inverted_index":{"Abstract":[0],"The":[1,142,186,251],"decorrelating":[2],"property":[3],"of":[4,28,43,52,73,84,228,253,265],"the":[5,17,21,29,36,40,48,85,97,116,155,209,226,246,260,263,266],"discrete":[6,175],"wavelet":[7,156,172,176],"transformation":[8],"(DWT)":[9],"appears":[10],"valuable":[11],"because":[12],"one":[13],"can":[14],"avoid":[15],"estimating":[16],"correlation":[18,41,50],"structure":[19,42,51],"in":[20,89,123,154,168],"original":[22,53],"data":[23,83],"space":[24],"by":[25,208,242],"bootstrap":[26,152],"resampling":[27,153],"DWT.":[30],"Several":[31],"authors":[32,187],"have":[33],"shown":[34],"that":[35,68,87,96],"wavestrap":[37,98,117],"approximately":[38],"retains":[39],"observations.":[44],"However,":[45],"simply":[46],"retaining":[47],"same":[49],"observations":[54],"does":[55,99,256],"not":[56,100,120,257],"guarantee":[57],"enough":[58],"variation":[59],"for":[60,75,80,105,137,144,198],"regression":[61,79,129],"parameter":[62],"estimators.":[63],"Our":[64],"simulation":[65],"studies":[66],"show":[67],"these":[69,145,164],"wavestraps":[70],"yield":[71],"undercoverage":[72],"parameters":[74],"a":[76,222,243],"simple":[77],"linear":[78,128],"time":[81],"series":[82],"type":[86],"arise":[88],"functional":[90],"MRI":[91],"experiments.":[92],"It":[93],"is":[94,119,158],"disappointing":[95],"even":[101],"provide":[102],"valid":[103,122],"resamples":[104,125],"both":[106],"white":[107],"noise":[108,113],"sequences":[109],"and":[110,131,195,202,214,219,241,269],"fractional":[111],"Brownian":[112],"sequences.":[114],"Thus,":[115],"method":[118],"completely":[121],"obtaining":[124],"related":[126],"to":[127,160,190],"analysis":[130],"should":[132,273],"be":[133,274],"used":[134],"with":[135,225],"caution":[136],"hypothesis":[138],"testing":[139],"as":[140],"well.":[141],"reasons":[143],"undercoverages":[146],"are":[147],"also":[148],"discussed.":[149],"A":[150],"parametric":[151],"domain":[157],"introduced":[159],"offer":[161],"insight":[162],"into":[163],"previously":[165],"undiscovered":[166],"defects":[167],"wavestrapping.":[169],"Keywords:":[170],"BootstrapDiscrete":[171],"transform":[173,177],"(DWT)fMRIInverse":[174],"(IDWT)Permutation":[178],"testsWavestrapMathematics":[179],"Subject":[180],"Classification:":[181],"Primary":[182],"62G09Secondary":[183],"62P10":[184],"Acknowledgment":[185],"would":[188],"like":[189],"thank":[191],"an":[192],"associate":[193],"editor":[194],"two":[196],"referees":[197],"their":[199],"constructive":[200],"comments":[201],"suggestions.":[203],"This":[204],"study":[205],"was":[206],"supported":[207],"U.S.":[210,235,267],"Army":[211],"Medical":[212,231],"Research":[213],"Material":[215],"Command":[216],"numbers":[217],"DAMD17-97-7-7024":[218],"DAMD17-01-1-0741":[220],"through":[221],"consortium":[223],"agreement":[224],"University":[227],"Texas":[229],"Southwestern":[230],"Center":[232],"at":[233],"Dallas,":[234,249],"Public":[236],"Health":[237],"Service":[238],"grant":[239,244],"MO1-RR00633,":[240],"from":[245],"Perot":[247],"Foundation,":[248],"Texas.":[250],"content":[252],"this":[254],"paper":[255],"necessarity":[258],"reflect":[259],"position":[261],"or":[262],"policy":[264],"government,":[268],"no":[270],"official":[271],"endorsement":[272],"inferred.":[275]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2026-02-08T09:19:03.324500","created_date":"2025-10-10T00:00:00"}