{"id":"https://openalex.org/W4248960752","doi":"https://doi.org/10.1002/9780470050118.ecse349","title":"Regression Analysis","display_name":"Regression Analysis","publication_year":2007,"publication_date":"2007-12-06","ids":{"openalex":"https://openalex.org/W4248960752","doi":"https://doi.org/10.1002/9780470050118.ecse349"},"language":"en","primary_location":{"id":"doi:10.1002/9780470050118.ecse349","is_oa":false,"landing_page_url":"https://doi.org/10.1002/9780470050118.ecse349","pdf_url":null,"source":{"id":"https://openalex.org/S4306534807","display_name":"Wiley Encyclopedia of Computer Science and Engineering","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wiley Encyclopedia of Computer Science and Engineering","raw_type":"other"},"type":"other","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/A5010159707","display_name":"Sanford Weisberg","orcid":"https://orcid.org/0000-0002-1141-6699"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sanford Weisberg","raw_affiliation_strings":["University of Minnesota, School of Statistics, Minneapolis, Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, School of Statistics, Minneapolis, Minnesota","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5010159707"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.995199978351593,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.995199978351593,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9562000036239624,"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/T13141","display_name":"Statistical Methods and Applications","score":0.9509000182151794,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/regression-diagnostic","display_name":"Regression diagnostic","score":0.6697450280189514},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.6083177924156189},{"id":"https://openalex.org/keywords/nonparametric-regression","display_name":"Nonparametric regression","score":0.596932053565979},{"id":"https://openalex.org/keywords/proper-linear-model","display_name":"Proper linear model","score":0.589417040348053},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5809762477874756},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.580512285232544},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5677105188369751},{"id":"https://openalex.org/keywords/cross-sectional-regression","display_name":"Cross-sectional regression","score":0.5625290274620056},{"id":"https://openalex.org/keywords/simple-linear-regression","display_name":"Simple linear regression","score":0.5543842315673828},{"id":"https://openalex.org/keywords/local-regression","display_name":"Local regression","score":0.5202288031578064},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.4833669066429138},{"id":"https://openalex.org/keywords/segmented-regression","display_name":"Segmented regression","score":0.4672873616218567},{"id":"https://openalex.org/keywords/factor-regression-model","display_name":"Factor regression model","score":0.46600207686424255},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.4587469696998596},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.40170568227767944},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3628140091896057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35534876585006714},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34447187185287476}],"concepts":[{"id":"https://openalex.org/C57381214","wikidata":"https://www.wikidata.org/wiki/Q55631393","display_name":"Regression diagnostic","level":4,"score":0.6697450280189514},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6083177924156189},{"id":"https://openalex.org/C74127309","wikidata":"https://www.wikidata.org/wiki/Q3455886","display_name":"Nonparametric regression","level":3,"score":0.596932053565979},{"id":"https://openalex.org/C32224588","wikidata":"https://www.wikidata.org/wiki/Q7250175","display_name":"Proper linear model","level":4,"score":0.589417040348053},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5809762477874756},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.580512285232544},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5677105188369751},{"id":"https://openalex.org/C90157343","wikidata":"https://www.wikidata.org/wiki/Q5188196","display_name":"Cross-sectional regression","level":4,"score":0.5625290274620056},{"id":"https://openalex.org/C149769383","wikidata":"https://www.wikidata.org/wiki/Q7520804","display_name":"Simple linear regression","level":3,"score":0.5543842315673828},{"id":"https://openalex.org/C60316415","wikidata":"https://www.wikidata.org/wiki/Q6664520","display_name":"Local regression","level":4,"score":0.5202288031578064},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.4833669066429138},{"id":"https://openalex.org/C35519122","wikidata":"https://www.wikidata.org/wiki/Q3775699","display_name":"Segmented regression","level":4,"score":0.4672873616218567},{"id":"https://openalex.org/C93698799","wikidata":"https://www.wikidata.org/wiki/Q5428730","display_name":"Factor regression model","level":5,"score":0.46600207686424255},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.4587469696998596},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.40170568227767944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3628140091896057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35534876585006714},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34447187185287476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/9780470050118.ecse349","is_oa":false,"landing_page_url":"https://doi.org/10.1002/9780470050118.ecse349","pdf_url":null,"source":{"id":"https://openalex.org/S4306534807","display_name":"Wiley Encyclopedia of Computer Science and Engineering","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wiley Encyclopedia of Computer Science and Engineering","raw_type":"other"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W171677499","https://openalex.org/W1570472658","https://openalex.org/W1594031697","https://openalex.org/W1603903339","https://openalex.org/W1608582612","https://openalex.org/W1974791250","https://openalex.org/W1998613841","https://openalex.org/W2021136548","https://openalex.org/W2065540158","https://openalex.org/W2070779353","https://openalex.org/W2071020270","https://openalex.org/W2075665712","https://openalex.org/W2076983043","https://openalex.org/W2091982937","https://openalex.org/W2099427332","https://openalex.org/W2486008048","https://openalex.org/W2492294785","https://openalex.org/W3106889297","https://openalex.org/W4233620411","https://openalex.org/W4237210482","https://openalex.org/W4242484299","https://openalex.org/W4295134715","https://openalex.org/W4299689471","https://openalex.org/W4301861531","https://openalex.org/W4302594429"],"related_works":["https://openalex.org/W603221366","https://openalex.org/W4251253833","https://openalex.org/W600390644","https://openalex.org/W4256497325","https://openalex.org/W2353842888","https://openalex.org/W2374894797","https://openalex.org/W4238233914","https://openalex.org/W1496469336","https://openalex.org/W2886532972","https://openalex.org/W1536189117"],"abstract_inverted_index":{"Abstract":[0],"In":[1],"statistics,":[2],"regression":[3,46,53,71,99],"is":[4,72,81],"the":[5,8,11,17,49,79],"study":[6],"of":[7,13,19,21,33,52],"changes":[9],"in":[10,29,39,67,98],"distribution":[12],"a":[14,82,85],"response":[15,80],"as":[16],"values":[18],"predictors":[20],"it":[22],"are":[23,27,48,65],"varied.":[24],"Regression":[25],"models":[26],"used":[28,59],"virtually":[30],"all":[31],"areas":[32],"science":[34],"and":[35,43,64],"represent":[36],"fundamental":[37],"tools":[38,51],"understanding":[40],"data.":[41],"Simple":[42],"multiple":[44],"linear":[45],"methodology":[47],"basic":[50],"analysis.":[54],"These":[55],"methods":[56,91],"can":[57],"be":[58],"with":[60],"only":[61],"minimal":[62],"assumptions":[63],"described":[66],"this":[68],"article.":[69],"Linear":[70],"not":[73],"always":[74],"appropriate,":[75],"for":[76],"example,":[77],"if":[78],"category":[83],"or":[84],"count.":[86],"For":[87],"these":[88],"cases,":[89],"specialized":[90],"have":[92],"been":[93],"developed.":[94],"More":[95],"recent":[96],"developments":[97],"include":[100],"nonparametric,":[101],"semiparametric":[102],"approaches,":[103],"among":[104],"others.":[105]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}