{"title":"Estimation of Software Size and Effort Distributions Using Paired Ratio Comparison Matrices","authors":"K. Lum, J. Hihn","doi":"10.1080/10157891.2007.10462278","DOIUrl":null,"url":null,"abstract":"This paper describes the approach and algorithms used to generalize the paired ratio comparison matrix technique to use information inherent in multiple estimates, multiple reference projects, and estimator range information to generate estimated effort and size distributions.","PeriodicalId":311790,"journal":{"name":"Journal of Parametrics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Parametrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10157891.2007.10462278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper describes the approach and algorithms used to generalize the paired ratio comparison matrix technique to use information inherent in multiple estimates, multiple reference projects, and estimator range information to generate estimated effort and size distributions.