{"id":"https://openalex.org/W2051218140","doi":"https://doi.org/10.1137/s1064827595290462","title":"Efficient Nonparametric Density Estimation on the Sphere with Applications in Fluid Mechanics","display_name":"Efficient Nonparametric Density Estimation on the Sphere with Applications in Fluid Mechanics","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W2051218140","doi":"https://doi.org/10.1137/s1064827595290462","mag":"2051218140"},"language":"en","primary_location":{"id":"doi:10.1137/s1064827595290462","is_oa":false,"landing_page_url":"https://doi.org/10.1137/s1064827595290462","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","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/A5083097406","display_name":"\u00d6mer Eugeciouglu","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"\u00d6mer Eugeciouglu","raw_affiliation_strings":["Department of Computer Science, University of California, Santa Barbara, CA 93106"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Santa Barbara, CA 93106","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081004875","display_name":"Ashok Srinivasan","orcid":"https://orcid.org/0000-0003-0408-2886"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashok Srinivasan","raw_affiliation_strings":["Department of Mathematics, Indian Institute of Technology, Bombay, India"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Indian Institute of Technology, Bombay, India","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083097406"],"corresponding_institution_ids":["https://openalex.org/I154570441"],"apc_list":null,"apc_paid":null,"fwci":0.5907,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.69740699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"22","issue":"1","first_page":"152","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9750999808311462,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.8022584319114685},{"id":"https://openalex.org/keywords/multivariate-kernel-density-estimation","display_name":"Multivariate kernel density estimation","score":0.7681957483291626},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7653788328170776},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.7280007600784302},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7083845734596252},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6778606176376343},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.658147394657135},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.6109366416931152},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5674907565116882},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5348718166351318},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.5008857250213623},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.45546919107437134},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.44910168647766113},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4389110803604126},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39425766468048096},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.21523070335388184},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1696612536907196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08522742986679077},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.07944130897521973}],"concepts":[{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.8022584319114685},{"id":"https://openalex.org/C84894716","wikidata":"https://www.wikidata.org/wiki/Q6935135","display_name":"Multivariate kernel density estimation","level":5,"score":0.7681957483291626},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7653788328170776},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.7280007600784302},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7083845734596252},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6778606176376343},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.658147394657135},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.6109366416931152},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5674907565116882},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5348718166351318},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.5008857250213623},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.45546919107437134},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44910168647766113},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4389110803604126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39425766468048096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.21523070335388184},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1696612536907196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08522742986679077},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.07944130897521973},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/s1064827595290462","is_oa":false,"landing_page_url":"https://doi.org/10.1137/s1064827595290462","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","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":35,"referenced_works":["https://openalex.org/W204885769","https://openalex.org/W604181985","https://openalex.org/W1669135700","https://openalex.org/W1983207308","https://openalex.org/W1985905466","https://openalex.org/W1993934463","https://openalex.org/W1997225897","https://openalex.org/W2014268383","https://openalex.org/W2018538722","https://openalex.org/W2020929440","https://openalex.org/W2025392487","https://openalex.org/W2025779340","https://openalex.org/W2044118191","https://openalex.org/W2055657159","https://openalex.org/W2058440261","https://openalex.org/W2060471236","https://openalex.org/W2063667201","https://openalex.org/W2078886696","https://openalex.org/W2111548551","https://openalex.org/W2118020555","https://openalex.org/W2129905273","https://openalex.org/W2156339477","https://openalex.org/W2157005274","https://openalex.org/W2480304173","https://openalex.org/W2746996149","https://openalex.org/W2800501357","https://openalex.org/W2904863873","https://openalex.org/W3013267890","https://openalex.org/W3014646885","https://openalex.org/W3021622851","https://openalex.org/W3119264854","https://openalex.org/W4230813007","https://openalex.org/W4230941884","https://openalex.org/W4233014035","https://openalex.org/W4254932737"],"related_works":["https://openalex.org/W1569550976","https://openalex.org/W2355371556","https://openalex.org/W4386118679","https://openalex.org/W2051218140","https://openalex.org/W3121668058","https://openalex.org/W2113751036","https://openalex.org/W2105725268","https://openalex.org/W2060852468","https://openalex.org/W1190385587","https://openalex.org/W2142816366"],"abstract_inverted_index":{"The":[0,146],"application":[1],"of":[2,11,31,53,59,66,101,121,132,189],"nonparametric":[3,117,136],"probability":[4,67],"density":[5,30,68,77,103,137],"function":[6],"estimation":[7,65,78,138],"for":[8,72,135,143,164,174],"the":[9,29,32,40,44,51,57,60,76,85,89,102,106,114,186],"purpose":[10],"data":[12],"analysis":[13],"is":[14,70,79,140],"well":[15],"established.":[16],"More":[17],"recently,":[18],"such":[19,144],"methods":[20,155],"have":[21],"been":[22],"applied":[23],"to":[24,112,124,168,171],"fluid":[25,33],"flow":[26],"calculations":[27,45,74],"since":[28,75],"plays":[34],"a":[35,129,150],"crucial":[36,71],"role":[37],"in":[38,156],"determining":[39],"flow.":[41],"Furthermore,":[42],"when":[43],"involve":[46],"directional":[47],"or":[48],"axial":[49],"data,":[50],"domain":[52],"interest":[54],"falls":[55],"on":[56,181],"surface":[58],"sphere.":[61],"Accurate":[62],"and":[63,159,184],"fast":[64],"functions":[69,123,134],"these":[73],"performed":[80],"at":[81,105],"each":[82],"iteration":[83],"during":[84],"computation.":[86],"In":[87],"particular":[88],"values":[90],"fn":[91,94,99],"(X1":[92],"),":[93,96],"(X2":[95],"...":[97],",":[98],"(Xn)":[100],"estimate":[104],"sampled":[107],"points":[108],"Xi":[109],"are":[110],"needed":[111],"evolve":[113],"system.":[115],"Usual":[116],"estimators":[118],"make":[119],"use":[120],"kernel":[122,154,193],"construct":[125],"fn.":[126],"We":[127,177],"propose":[128],"special":[130],"sequence":[131],"weight":[133],"that":[139],"especially":[141],"suitable":[142],"applications.":[145],"resulting":[147],"method":[148,191],"has":[149],"computational":[151,187],"advantage":[152],"over":[153],"certain":[157],"situations":[158],"also":[160,178],"parallelizes":[161],"easily.":[162],"Conditions":[163],"convergence":[165],"turn":[166],"out":[167],"be":[169],"similar":[170],"those":[172],"required":[173],"kernel-based":[175],"methods.":[176],"discuss":[179],"experiments":[180],"different":[182],"distributions":[183],"compare":[185],"efficiency":[188],"our":[190],"with":[192],"based":[194],"estimators.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
