乐胖代购免代理版

{"id":"https://openalex.org/W2003826755","doi":"https://doi.org/10.1198/004017004000000455","title":"Phase I Analysis of Linear Profiles With Calibration Applications","display_name":"Phase I Analysis of Linear Profiles With Calibration Applications","publication_year":2004,"publication_date":"2004-10-19","ids":{"openalex":"https://openalex.org/W2003826755","doi":"https://doi.org/10.1198/004017004000000455","mag":"2003826755"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017004000000455","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5029826752","display_name":"Mahmoud A. Mahmoud","orcid":"https://orcid.org/0000-0003-4753-5195"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahmoud A Mahmoud","raw_affiliation_strings":["Department of Statistics Virginia Tech Blacksburg, VA 24061"],"affiliations":[{"raw_affiliation_string":"Department of Statistics Virginia Tech Blacksburg, VA 24061","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055123256","display_name":"William H. Woodall","orcid":"https://orcid.org/0000-0002-9962-0001"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William H Woodall","raw_affiliation_strings":["Virginia Tech"],"affiliations":[{"raw_affiliation_string":"Virginia Tech","institution_ids":["https://openalex.org/I859038795"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.8,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":319,"citation_normalized_percentile":{"value":0.999555,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"46","issue":"4","first_page":"380","last_page":"391"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.9914,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9887,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44921732}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.682734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.60479444},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.54072326},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5385529},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4967199},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47824326},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44921732},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.39739248},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39089835},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36990905},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36064976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1818353},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16867489},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017004000000455","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":21,"referenced_works":["https://openalex.org/W1511738908","https://openalex.org/W1580673759","https://openalex.org/W1594791439","https://openalex.org/W1968632832","https://openalex.org/W1989638282","https://openalex.org/W2024192961","https://openalex.org/W2047741328","https://openalex.org/W2092592462","https://openalex.org/W2095453734","https://openalex.org/W2107146446","https://openalex.org/W2108623391","https://openalex.org/W2116798985","https://openalex.org/W2122450421","https://openalex.org/W2132121707","https://openalex.org/W2139356790","https://openalex.org/W2163990027","https://openalex.org/W2335587011","https://openalex.org/W2898519191","https://openalex.org/W4251895690","https://openalex.org/W47198768","https://openalex.org/W64578218"],"related_works":["https://openalex.org/W2594414941","https://openalex.org/W2555586164","https://openalex.org/W2382169280","https://openalex.org/W2365607528","https://openalex.org/W2365102679","https://openalex.org/W2114770238","https://openalex.org/W2074939091","https://openalex.org/W2046724649","https://openalex.org/W2043347519","https://openalex.org/W1499374895"],"abstract_inverted_index":{"We":[0,22,68,83,116],"study":[1],"the":[2,9,52,57,63,66,98,110,124,132,140],"phase":[3],"I":[4],"analysis":[5],"of":[6,11,35,54,56,65,97,100,106,112,139],"data":[7,28],"when":[8],"quality":[10],"a":[12,19,32,40,47,71,79,101,144],"process":[13,114,133],"or":[14],"product":[15],"is":[16],"characterized":[17],"by":[18],"linear":[20,26],"function.":[21],"assume":[23],"that":[24,85,119],"simple":[25],"regression":[27,81],"are":[29,126],"available":[30],"for":[31,103],"fixed":[33],"number":[34],"samples":[36],"collected":[37],"over":[38],"time,":[39],"situation":[41],"common":[42],"in":[43,78,95,123,128,131],"calibration":[44,145],"applications.":[45],"Using":[46],"simulation":[48],"study,":[49],"we":[50,136],"compare":[51],"performance":[53,90],"some":[55,138],"recommended":[58],"approaches":[59],"used":[60],"to":[61,92,143],"assess":[62],"stability":[64],"process.":[67],"also":[69,117],"propose":[70],"method":[72,87],"based":[73],"on":[74],"using":[75],"indicator":[76],"variables":[77],"multiple":[80],"model.":[82],"show":[84,118],"this":[86],"has":[88],"competitive":[89],"relative":[91],"other":[93],"methods":[94,121,142],"terms":[96],"probability":[99],"signal":[102],"certain":[104],"types":[105],"parameter":[107],"shifts":[108,130],"within":[109],"set":[111],"historical":[113],"data.":[115],"two":[120],"proposed":[122,141],"literature":[125],"ineffective":[127],"detecting":[129],"parameters.":[134],"Finally,":[135],"apply":[137],"example.":[146]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2003826755","counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":21},{"year":2014,"cited_by_count":37},{"year":2013,"cited_by_count":20},{"year":2012,"cited_by_count":24}],"updated_date":"2025-01-06T18:48:25.081096","created_date":"2016-06-24"}