BOOTSTRAP CONFIDENCE-INTERVALS FOR THE MINIMUM SUM OF ABSOLUTE ERRORS REGRESSION

dc.creatorSTANGENHAUS, G
dc.creatorNARULA, SC
dc.creatorFERREIRA, P
dc.date1993
dc.date2014-08-01T18:23:35Z
dc.date2015-11-26T17:01:08Z
dc.date2014-08-01T18:23:35Z
dc.date2015-11-26T17:01:08Z
dc.date.accessioned2018-03-28T23:48:58Z
dc.date.available2018-03-28T23:48:58Z
dc.identifierJournal Of Statistical Computation And Simulation. Gordon Breach Sci Publ Ltd, v. 48, n. 41732, n. 127, n. 133, 1993.
dc.identifier0094-9655
dc.identifierWOS:A1993QM98400001
dc.identifier10.1080/00949659308811546
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/78205
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/78205
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1278649
dc.descriptionAt present very little is known about inference procedures on the parameters of the minimum sum of absolute errors, MSAE, regression model for small to medium size samples. We propose the use of bootstrap methods for this purpose. The (1 - alpha) confidence intervals on the parameters of the regression model may be constructed by using the bootstrap standard deviation or the bootstrap sampling distribution of the MSAE estimator. We compare and contrast the performance and quality of the intervals obtained by the two methods via a Monte Carlo study.
dc.description48
dc.description41732
dc.description127
dc.description133
dc.languageen
dc.publisherGordon Breach Sci Publ Ltd
dc.publisherReading
dc.publisherInglaterra
dc.relationJournal Of Statistical Computation And Simulation
dc.relationJ. Stat. Comput. Simul.
dc.rightsfechado
dc.sourceWeb of Science
dc.subjectINFERENCE PROCEDURES
dc.subjectHYPOTHESIS TESTING
dc.subjectL(1)-NORM
dc.subjectMONTE CARLO
dc.subjectPERCENTILE METHOD
dc.subjectInference Procedures
dc.titleBOOTSTRAP CONFIDENCE-INTERVALS FOR THE MINIMUM SUM OF ABSOLUTE ERRORS REGRESSION
dc.typeArtículos de revistas


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