{"id":"https://openalex.org/W2078261608","doi":"https://doi.org/10.1145/2339530.2339761","title":"Fast algorithms for comprehensive n-point correlation estimates","display_name":"Fast algorithms for comprehensive n-point correlation estimates","publication_year":2012,"publication_date":"2012-08-12","ids":{"openalex":"https://openalex.org/W2078261608","doi":"https://doi.org/10.1145/2339530.2339761","mag":"2078261608"},"language":"en","primary_location":{"id":"doi:10.1145/2339530.2339761","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2339530.2339761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-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/A5077464013","display_name":"William B. March","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"William B. March","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","Georgia Institute of Technology Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051565479","display_name":"Andrew J. Connolly","orcid":"https://orcid.org/0000-0001-5576-8189"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew J. Connolly","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005255629","display_name":"Alexander Gray","orcid":"https://orcid.org/0000-0003-0337-7359"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander G. Gray","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","Georgia Institute of Technology Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077464013"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":4.8246,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.94981324,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1478","last_page":"1486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9872000217437744,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9847999811172485,"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/variance","display_name":"Variance (accounting)","score":0.6008314490318298},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5832842588424683},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5580645203590393},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5505568385124207},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5026054382324219},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4885471761226654},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4811612069606781},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.43176013231277466},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33304211497306824},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.31529173254966736}],"concepts":[{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6008314490318298},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5832842588424683},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5580645203590393},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5505568385124207},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5026054382324219},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4885471761226654},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4811612069606781},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.43176013231277466},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33304211497306824},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31529173254966736},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2339530.2339761","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2339530.2339761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W1559625575","https://openalex.org/W1631457557","https://openalex.org/W1634692241","https://openalex.org/W1660301404","https://openalex.org/W1661802657","https://openalex.org/W1775163074","https://openalex.org/W1819393351","https://openalex.org/W1950647942","https://openalex.org/W1964260410","https://openalex.org/W1974586237","https://openalex.org/W1979902273","https://openalex.org/W1985461619","https://openalex.org/W2005314985","https://openalex.org/W2008323937","https://openalex.org/W2017539116","https://openalex.org/W2021943013","https://openalex.org/W2024668293","https://openalex.org/W2025634246","https://openalex.org/W2045915974","https://openalex.org/W2051694884","https://openalex.org/W2051869499","https://openalex.org/W2070238200","https://openalex.org/W2143022286","https://openalex.org/W2146558186","https://openalex.org/W2149684715","https://openalex.org/W2157246770","https://openalex.org/W2327078754","https://openalex.org/W2504619654","https://openalex.org/W2911302472","https://openalex.org/W2981570800","https://openalex.org/W3023398975","https://openalex.org/W3099250505","https://openalex.org/W3102765935","https://openalex.org/W3102797967","https://openalex.org/W3143789982","https://openalex.org/W3161326878","https://openalex.org/W3165771198","https://openalex.org/W6681144579","https://openalex.org/W6681402394","https://openalex.org/W6723266976","https://openalex.org/W6775503386"],"related_works":["https://openalex.org/W4234874385","https://openalex.org/W2323648130","https://openalex.org/W2157140558","https://openalex.org/W2378782423","https://openalex.org/W2388988621","https://openalex.org/W2357797405","https://openalex.org/W2366623913","https://openalex.org/W2374905595","https://openalex.org/W2516693588","https://openalex.org/W2116112408"],"abstract_inverted_index":{"The":[0],"n-point":[1],"correlation":[2],"functions":[3,19],"(npcf)":[4],"are":[5,20],"powerful":[6],"spatial":[7],"statistics":[8],"capable":[9],"of":[10,15,65,70,142],"fully":[11],"characterizing":[12],"any":[13],"set":[14],"multidimensional":[16],"points.":[17],"These":[18],"critical":[21],"in":[22,26,74,130,145],"key":[23],"data":[24,144],"analyses":[25],"astronomy":[27],"and":[28,47,52,94,137],"materials":[29],"science,":[30],"among":[31],"other":[32],"fields,":[33],"for":[34,91,126],"example":[35],"to":[36,48,61,111,132,147],"test":[37],"whether":[38],"two":[39],"point":[40],"sets":[41],"come":[42],"from":[43],"the":[44,56,63,71,81,106,149],"same":[45],"distribution":[46],"validate":[49],"physical":[50],"models":[51],"theories.":[53],"For":[54],"example,":[55],"npcf":[57,83],"has":[58],"been":[59],"used":[60],"study":[62],"phenomenon":[64],"dark":[66],"energy,":[67],"considered":[68],"one":[69],"major":[72],"breakthroughs":[73],"recent":[75],"scientific":[76,117],"discoveries.":[77],"Unfortunately,":[78],"directly":[79],"estimating":[80],"continuous":[82],"at":[84],"a":[85,134],"single":[86],"value":[87],"requires":[88],"O(Nn)":[89],"time":[90],"$N$":[92],"points,":[93],"n":[95],"may":[96],"be":[97],"2,":[98],"3,":[99],"4":[100],"or":[101],"even":[102],"higher,":[103],"depending":[104],"on":[105],"sensitivity":[107],"required.":[108],"In":[109],"order":[110,131,146],"draw":[112],"useful":[113],"conclusions":[114],"about":[115],"real":[116],"problems,":[118],"we":[119],"must":[120],"repeat":[121],"this":[122],"expensive":[123],"computation":[124],"both":[125],"many":[127,139],"different":[128,140],"scales":[129],"derive":[133],"smooth":[135],"estimate":[136],"over":[138],"subsamples":[141],"our":[143],"bound":[148],"variance.":[150]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}