{"id":"https://openalex.org/W18129694","doi":null,"title":"Computational Issues for Quantile Regression","display_name":"Computational Issues for Quantile Regression","publication_year":2005,"publication_date":"2005-01-01","ids":{"openalex":"https://openalex.org/W18129694","mag":"18129694"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.125.5496","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.125.5496","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://sankhya.isical.ac.in/search/67_2/2005018.pdf","raw_type":"text"},"parent_works":[],"lineage":["https://openalex.org/W18129694"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":[],"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/A5074256229","display_name":"Colin Chen","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Colin Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5055029890","display_name":"Ying Wei","orcid":"https://orcid.org/0000-0002-7164-8109","observed_orcids":["https://orcid.org/0000-0002-7164-8109"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying Wei","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7164-8109","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.62,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.66638522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":92,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9595000147819519,"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":0.9595000147819519,"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":0.0340999998152256,"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/T13487","display_name":"Statistical and numerical algorithms","score":0.0015999999595806003,"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/quantile-regression","display_name":"quantile regression","score":1.0},{"id":"https://openalex.org/keywords/computer-algorithms","display_name":"computational algorithms","score":0.8199999928474426},{"id":"https://openalex.org/keywords/simplex-algorithm","display_name":"simplex algorithm","score":0.8650000095367432},{"id":"https://openalex.org/keywords/interior-point-methods","display_name":"interior point methods","score":0.7609999775886536},{"id":"https://openalex.org/keywords/smoothing-algorithms","display_name":"smoothing algorithms","score":0.8610000014305115},{"id":"https://openalex.org/keywords/optimization","display_name":"optimization","score":0.6620000004768372},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"parallel computing","score":0.7360000014305115},{"id":"https://openalex.org/keywords/sparse-computation","display_name":"sparse computation","score":0.9779999852180481},{"id":"https://openalex.org/keywords/confidence-intervals","display_name":"confidence intervals","score":0.9210000038146973},{"id":"https://openalex.org/keywords/resampling","display_name":"resampling","score":0.8980000019073486},{"id":"https://openalex.org/keywords/high-dimensional-covariates","display_name":"high-dimensional covariates","score":0.9330000281333923}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6674849390983582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6022390723228455},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.5943528413772583},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.5835371017456055},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5006287097930908},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.499439001083374},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.4913589060306549},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.4583333134651184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4349534511566162},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.4184987246990204},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41251814365386963},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.367009699344635},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32451796531677246},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2948800325393677},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20779278874397278},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.125.5496","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.125.5496","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://sankhya.isical.ac.in/search/67_2/2005018.pdf","raw_type":"text"},{"id":"mag:18129694","doi":null,"is_oa":false,"landing_page_url":"http://sankhya.isical.ac.in/search/67_2/2005018.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W138820251","https://openalex.org/W1575013331","https://openalex.org/W1691300750","https://openalex.org/W1992015234","https://openalex.org/W2033158547","https://openalex.org/W2047827159","https://openalex.org/W2048245744","https://openalex.org/W2054113207","https://openalex.org/W2075754144","https://openalex.org/W2086847993","https://openalex.org/W2118711140","https://openalex.org/W2466564333","https://openalex.org/W2611147814"],"related_works":["https://openalex.org/W2046271091","https://openalex.org/W138820251","https://openalex.org/W2022518389","https://openalex.org/W932097805","https://openalex.org/W2892323701","https://openalex.org/W60170727","https://openalex.org/W2114929332","https://openalex.org/W1996905516","https://openalex.org/W200887292"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,24,60],"discuss":[4,40,66],"some":[5,43],"practical":[6],"computational":[7],"issues":[8],"for":[9,77],"quantile":[10],"regression.":[11],"We":[12,33,65],"consider":[13],"the":[14],"computation":[15],"from":[16],"two":[17],"aspects:":[18],"estimation":[19],"and":[20,31,35,50,71],"inference.":[21],"For":[22,58],"estimation,":[23],"cover":[25],"three":[26,67],"algorithms:":[27],"simplex,":[28],"interior":[29],"point,":[30],"smoothing.":[32],"describe":[34],"compare":[36],"these":[37,54],"algorithms,":[38],"then":[39],"implementation":[41],"of":[42,84],"computing":[44],"techniques,":[45],"which":[46],"include":[47],"optimization,":[48],"parallelization,":[49],"sparse":[51],"computation,":[52],"with":[53,80],"algorithms":[55],"in":[56],"practice.":[57],"inference,":[59],"focus":[61],"on":[62],"confidence":[63],"intervals.":[64],"methods:":[68],"sparsity,":[69],"rank-score,":[70],"resampling.":[72],"Their":[73],"performances":[74],"are":[75],"compared":[76],"data":[78],"sets":[79],"a":[81],"large":[82],"number":[83],"covariates.":[85],"AMS":[86],"(2000)":[87],"subject":[88],"classification.":[89],"Primary":[90],"62F35;":[91],"secondary":[92],"62J99.":[93]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":7}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2016-06-24T00:00:00"}