{"id":"https://openalex.org/W2106459314","doi":"https://doi.org/10.1109/cmpsac.2004.1342843","title":"Software effort prediction models using maximum likelihood methods require multivariate normality of the software metrics data sample:can such a sample be made multivariate normal?","display_name":"Software effort prediction models using maximum likelihood methods require multivariate normality of the software metrics data sample:can such a sample be made multivariate normal?","publication_year":2004,"publication_date":"2004-11-08","ids":{"openalex":"https://openalex.org/W2106459314","doi":"https://doi.org/10.1109/cmpsac.2004.1342843","mag":"2106459314"},"language":"en","primary_location":{"id":"doi:10.1109/cmpsac.2004.1342843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cmpsac.2004.1342843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th Annual International Computer Software and Applications Conference, 2004. COMPSAC 2004.","raw_type":"proceedings-article"},"type":"conference-paper","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/A5022687207","display_name":"Victor K. Y. Chan","orcid":"https://orcid.org/0000-0002-3755-4512"},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":true,"raw_author_name":"V.K.Y. Chan","raw_affiliation_strings":["Macao Polytechnic Institute, Macao, China","Macau Polytech. Inst"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macao Polytechnic Institute, Macao, China","institution_ids":["https://openalex.org/I49835588"]},{"raw_affiliation_string":"Macau Polytech. Inst","institution_ids":["https://openalex.org/I49835588"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022687207"],"corresponding_institution_ids":["https://openalex.org/I49835588"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"274","last_page":"279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12423","display_name":"Software Reliability and Analysis Research","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10430","display_name":"Software Engineering Techniques and Practices","score":0.9185000061988831,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7223600745201111},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6617813110351562},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.641421914100647},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.6413710117340088},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6114907264709473},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5991179943084717},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.4743337035179138},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.45553210377693176},{"id":"https://openalex.org/keywords/normality","display_name":"Normality","score":0.4486366808414459},{"id":"https://openalex.org/keywords/multivariate-analysis","display_name":"Multivariate analysis","score":0.44553306698799133},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4160469174385071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3164806663990021},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19701972603797913}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7223600745201111},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6617813110351562},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.641421914100647},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.6413710117340088},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6114907264709473},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5991179943084717},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.4743337035179138},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.45553210377693176},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.4486366808414459},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.44553306698799133},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4160469174385071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3164806663990021},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19701972603797913},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cmpsac.2004.1342843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cmpsac.2004.1342843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th Annual International Computer Software and Applications Conference, 2004. COMPSAC 2004.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W100273097","https://openalex.org/W1619356713","https://openalex.org/W1990994334","https://openalex.org/W1995880999","https://openalex.org/W2007735936","https://openalex.org/W2011882477","https://openalex.org/W2044758663","https://openalex.org/W2065262588","https://openalex.org/W2092897775","https://openalex.org/W2095778055","https://openalex.org/W2105586900","https://openalex.org/W2136691316","https://openalex.org/W2155725368","https://openalex.org/W2157542847","https://openalex.org/W2167110832","https://openalex.org/W2319794630","https://openalex.org/W2480680997","https://openalex.org/W3016054986","https://openalex.org/W6604041265","https://openalex.org/W6653474385"],"related_works":["https://openalex.org/W2220190985","https://openalex.org/W2346846619","https://openalex.org/W2019273819","https://openalex.org/W2417295580","https://openalex.org/W4245691902","https://openalex.org/W1840639769","https://openalex.org/W4250921637","https://openalex.org/W2033612661","https://openalex.org/W4237200122","https://openalex.org/W2055354074"],"abstract_inverted_index":{"Missing":[0],"data":[1,7,35,53,78,94,115],"often":[2],"appear":[3],"in":[4,125],"software":[5,12,113,135],"metrics":[6,114],"samples":[8,54,116],"used":[9],"to":[10,91,109],"construct":[11],"effort":[13,136],"prediction":[14,137],"models.":[15],"So":[16],"far,":[17],"the":[18,23,43,52,56,69,76,93,97,118],"least":[19],"biased":[20],"and":[21,83,117,130],"thus":[22],"most":[24],"strongly":[25],"recommended":[26],"family":[27],"of":[28,32,45,71,99,134],"such":[29,46,65,72,101,122],"models":[30,66,138],"capable":[31],"handling":[33],"missing":[34],"are":[36,59],"those":[37],"using":[38,139],"maximum":[39,47,140],"likelihood":[40,48,141],"methods.":[41],"However,":[42],"theory":[44],"methods":[49,142],"assumes":[50],"that":[51],"underlying":[55],"model":[57],"construction":[58],"multivariate":[60],"normal.":[61],"Previous":[62],"research":[63,128],"on":[64,129],"simply":[67],"ignored":[68],"violation":[70],"an":[73,102],"assumption":[74],"by":[75],"empirical":[77],"samples.":[79],"This":[80,104],"paper":[81],"proposes":[82],"empirically":[84,107],"illustrates":[85],"a":[86,123],"not-so-complicated":[87],"but":[88],"effective":[89],"technique":[90,105,124],"transform":[92],"sample":[95],"for":[96,111],"purpose":[98],"meeting":[100],"assumption.":[103],"is":[106],"proven":[108],"work":[110],"typical":[112],"author":[119],"recommends":[120],"applying":[121],"any":[126],"further":[127],"practical":[131],"industrial":[132],"application":[133]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
