{"id":"https://openalex.org/W2572211505","doi":"https://doi.org/10.1201/b19567-22","title":"Estimator and Model Selection Using Cross-Validation Iva\u00b4n D\u0131\u00b4az","display_name":"Estimator and Model Selection Using Cross-Validation Iva\u00b4n D\u0131\u00b4az","publication_year":2016,"publication_date":"2016-02-22","ids":{"openalex":"https://openalex.org/W2572211505","doi":"https://doi.org/10.1201/b19567-22","mag":"2572211505"},"language":"en","primary_location":{"id":"doi:10.1201/b19567-22","is_oa":false,"landing_page_url":"https://doi.org/10.1201/b19567-22","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Handbook of Big Data","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8733,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.87844037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"239","last_page":"256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.996999979019165,"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":0.996999979019165,"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/T11236","display_name":"Control Systems and Identification","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9958000183105469,"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/cross-validation","display_name":"Cross-validation","score":0.6121783256530762},{"id":"https://openalex.org/keywords/model-validation","display_name":"Model validation","score":0.5823110342025757},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.5425655245780945},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5219932794570923},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5073022246360779},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4049479067325592},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3791428804397583},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2635582685470581},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1780487298965454},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.08567571640014648}],"concepts":[{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.6121783256530762},{"id":"https://openalex.org/C3019813237","wikidata":"https://www.wikidata.org/wiki/Q65089264","display_name":"Model validation","level":2,"score":0.5823110342025757},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.5425655245780945},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5219932794570923},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5073022246360779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4049479067325592},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3791428804397583},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2635582685470581},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1780487298965454},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.08567571640014648}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1201/b19567-22","is_oa":false,"landing_page_url":"https://doi.org/10.1201/b19567-22","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Handbook of Big Data","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2566240941"],"related_works":["https://openalex.org/W816105089","https://openalex.org/W2100523380","https://openalex.org/W4381571012","https://openalex.org/W2951489751","https://openalex.org/W4318240167","https://openalex.org/W4234107176","https://openalex.org/W3048572280","https://openalex.org/W2019765489","https://openalex.org/W4253742790","https://openalex.org/W3011444647"],"abstract_inverted_index":{"Appendix":[0,69],"A:":[1],"R":[2],"Code":[3],".":[4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,81,82,83,84,85,86,87,88,89,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,179,180,181],"237":[68],"B:":[70],"Description":[71],"of":[72,75,184,197,230,236,246,255,258,282,284,292,296,313],"the":[73,76,214,231,253,256,305],"Variables":[74],"Example":[77],"in":[78,239,320],"Section":[79],"13.2":[80],"238":[90],"References":[91],"239Suppose":[169],"we":[170,263,309],"observe":[171],"an":[172,195],"independent":[173],"and":[174,190,218,286,299],"identically":[175],"distributed":[176],"sample":[177],"Z1,":[178],",":[182],"Zn":[183],"random":[185],"variables":[186],"with":[187,223],"distribution":[188,232],"P0,":[189,209],"assume":[191],"that":[192,204,211,266,315],"P0":[193],"is":[194,206,279,288],"element":[196],"a":[198,259,280,289],"statistical":[199],"model":[200],"M.":[201],"Suppose":[202],"also":[203],"nothing":[205],"known":[207],"about":[208,226],"so":[210],"M":[212],"represents":[213],"nonparametric":[215],"model.":[216],"Statistical":[217],"machine":[219],"learning":[220],"are":[221,242],"concerned":[222],"drawing":[224],"inferences":[225],"target":[227],"parameters":[228,237,265,314],"\u03b70":[229,245],"P0.":[233],"The":[234,294],"types":[235],"discussed":[238],"this":[240],"chapter":[241],"typically":[243],"functions":[244,283],"z,":[247],"which":[248],"can":[249],"be":[250,268,317],"represented":[251],"as":[252,319],"minimizer":[254],"expectation":[257],"loss":[260,290,300],"function.":[261],"Speci\ufb01cally,":[262],"consider":[264],"may":[267,316],"de\ufb01ned":[269,318],"as\u03b70":[270],"=":[271],"argmin":[272],"\u03b7\u2208F\u222b":[273],"L(z,":[274],"\u03b7)":[275],"dP0(z),":[276],"(13.1)where":[277],"F":[278,298],"space":[281,297],"z":[285],"L":[287,302],"function":[291,301],"interest.":[293],"choice":[295],"explicitly":[303],"de\ufb01nes":[304],"estimation":[306],"problem.":[307],"Below":[308],"discuss":[310],"some":[311],"examples":[312],"Equation":[321],"13.1.":[322]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
