{"id":"https://openalex.org/W2121488120","doi":"https://doi.org/10.3233/mas-2007-2202","title":"Equidistant regression modeling","display_name":"Equidistant regression modeling","publication_year":2007,"publication_date":"2007-06-28","ids":{"openalex":"https://openalex.org/W2121488120","doi":"https://doi.org/10.3233/mas-2007-2202","mag":"2121488120"},"language":"en","primary_location":{"id":"doi:10.3233/mas-2007-2202","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-2007-2202","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","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/A5046740664","display_name":"Stan Lipovetsky","orcid":"https://orcid.org/0000-0001-7131-243X"},"institutions":[{"id":"https://openalex.org/I276751011","display_name":"GfK (United States)","ror":"https://ror.org/00jprdp28","country_code":"US","type":"company","lineage":["https://openalex.org/I276751011","https://openalex.org/I4210167111"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Stan Lipovetsky","raw_affiliation_strings":["GfK Custom Research North America, 8401 Golden Valley Rd., Minneapolis, MN 55427, USA. E-mail: stan.lipovetsky@gfk.com","GfK Custom Research North America, 8401 Golden Valley Rd., Minneapolis, MN 55427, USA. E-mail: stan.lipovetsky@Gfk.com"],"affiliations":[{"raw_affiliation_string":"GfK Custom Research North America, 8401 Golden Valley Rd., Minneapolis, MN 55427, USA. E-mail: stan.lipovetsky@gfk.com","institution_ids":["https://openalex.org/I276751011"]},{"raw_affiliation_string":"GfK Custom Research North America, 8401 Golden Valley Rd., Minneapolis, MN 55427, USA. E-mail: stan.lipovetsky@Gfk.com","institution_ids":["https://openalex.org/I276751011"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5046740664"],"corresponding_institution_ids":["https://openalex.org/I276751011"],"apc_list":null,"apc_paid":null,"fwci":1.4663,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.84531293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2","issue":"2","first_page":"71","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9993000030517578,"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":0.9993000030517578,"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":0.995199978351593,"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/T13487","display_name":"Statistical and numerical algorithms","score":0.9660000205039978,"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/mathematics","display_name":"Mathematics","score":0.7476406097412109},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6653033494949341},{"id":"https://openalex.org/keywords/nonlinear-regression","display_name":"Nonlinear regression","score":0.6516605615615845},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.638496994972229},{"id":"https://openalex.org/keywords/ordinary-least-squares","display_name":"Ordinary least squares","score":0.6077645421028137},{"id":"https://openalex.org/keywords/equidistant","display_name":"Equidistant","score":0.5843096375465393},{"id":"https://openalex.org/keywords/absolute-deviation","display_name":"Absolute deviation","score":0.5678537487983704},{"id":"https://openalex.org/keywords/least-absolute-deviations","display_name":"Least absolute deviations","score":0.5665743350982666},{"id":"https://openalex.org/keywords/residual-sum-of-squares","display_name":"Residual sum of squares","score":0.5482594966888428},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.5246241688728333},{"id":"https://openalex.org/keywords/lack-of-fit-sum-of-squares","display_name":"Lack-of-fit sum of squares","score":0.5203151702880859},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.513282060623169},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5053539872169495},{"id":"https://openalex.org/keywords/total-least-squares","display_name":"Total least squares","score":0.504564642906189},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4988713264465332},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.49272778630256653},{"id":"https://openalex.org/keywords/non-linear-least-squares","display_name":"Non-linear least squares","score":0.4840547442436218},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4596305787563324},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.43389129638671875},{"id":"https://openalex.org/keywords/generalized-least-squares","display_name":"Generalized least squares","score":0.41758713126182556},{"id":"https://openalex.org/keywords/explained-sum-of-squares","display_name":"Explained sum of squares","score":0.39292609691619873},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10287114977836609}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7476406097412109},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6653033494949341},{"id":"https://openalex.org/C46889948","wikidata":"https://www.wikidata.org/wiki/Q2755024","display_name":"Nonlinear regression","level":3,"score":0.6516605615615845},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.638496994972229},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.6077645421028137},{"id":"https://openalex.org/C158245278","wikidata":"https://www.wikidata.org/wiki/Q4386982","display_name":"Equidistant","level":2,"score":0.5843096375465393},{"id":"https://openalex.org/C120934525","wikidata":"https://www.wikidata.org/wiki/Q849149","display_name":"Absolute deviation","level":2,"score":0.5678537487983704},{"id":"https://openalex.org/C31441030","wikidata":"https://www.wikidata.org/wiki/Q4291882","display_name":"Least absolute deviations","level":3,"score":0.5665743350982666},{"id":"https://openalex.org/C49392186","wikidata":"https://www.wikidata.org/wiki/Q15096882","display_name":"Residual sum of squares","level":4,"score":0.5482594966888428},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.5246241688728333},{"id":"https://openalex.org/C166811707","wikidata":"https://www.wikidata.org/wiki/Q6468669","display_name":"Lack-of-fit sum of squares","level":4,"score":0.5203151702880859},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.513282060623169},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5053539872169495},{"id":"https://openalex.org/C169241690","wikidata":"https://www.wikidata.org/wiki/Q7828122","display_name":"Total least squares","level":3,"score":0.504564642906189},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4988713264465332},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.49272778630256653},{"id":"https://openalex.org/C45923927","wikidata":"https://www.wikidata.org/wiki/Q3319230","display_name":"Non-linear least squares","level":3,"score":0.4840547442436218},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4596305787563324},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.43389129638671875},{"id":"https://openalex.org/C188649462","wikidata":"https://www.wikidata.org/wiki/Q2246261","display_name":"Generalized least squares","level":3,"score":0.41758713126182556},{"id":"https://openalex.org/C49847556","wikidata":"https://www.wikidata.org/wiki/Q3964631","display_name":"Explained sum of squares","level":2,"score":0.39292609691619873},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10287114977836609},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/mas-2007-2202","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-2007-2202","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W19621276","https://openalex.org/W1528905581","https://openalex.org/W1576534100","https://openalex.org/W1596490224","https://openalex.org/W1600769580","https://openalex.org/W1663973292","https://openalex.org/W1973937775","https://openalex.org/W1975835288","https://openalex.org/W1982407283","https://openalex.org/W2001619934","https://openalex.org/W2003198420","https://openalex.org/W2029082950","https://openalex.org/W2030490911","https://openalex.org/W2039111546","https://openalex.org/W2046824232","https://openalex.org/W2063973166","https://openalex.org/W2066387895","https://openalex.org/W2089349283","https://openalex.org/W2117752150","https://openalex.org/W2129905273","https://openalex.org/W2131368024","https://openalex.org/W2152207163","https://openalex.org/W2152701363","https://openalex.org/W2156909104","https://openalex.org/W2586654969","https://openalex.org/W2611591252","https://openalex.org/W2797583072","https://openalex.org/W3015463134","https://openalex.org/W3023786531"],"related_works":["https://openalex.org/W2040464743","https://openalex.org/W1991217434","https://openalex.org/W2525659285","https://openalex.org/W1780286370","https://openalex.org/W2392571216","https://openalex.org/W2034819163","https://openalex.org/W2083446492","https://openalex.org/W2154627047","https://openalex.org/W1542672284","https://openalex.org/W3097527465"],"abstract_inverted_index":{"A":[0],"criterion":[1],"of":[2],"equalizing":[3],"residual":[4],"squares":[5,20],"is":[6],"considered":[7],"for":[8],"regression":[9,25],"modeling,":[10],"and":[11,21],"its":[12],"results":[13],"are":[14],"compared":[15],"with":[16,32],"the":[17,33],"ordinary":[18],"least":[19,22],"absolute":[23],"deviations":[24],"models.":[26],"Equalized":[27],"residuals":[28],"yield":[29],"a":[30],"model":[31],"minimum":[34],"mean":[35],"di":[36]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}