Show simple item record

dc.contributor.advisorJirawan Jitthavechth
dc.contributor.authorSrisuda Boonyimth
dc.date.accessioned2022-05-09T04:40:46Z
dc.date.available2022-05-09T04:40:46Z
dc.date.issued2015th
dc.identifier.otherb191876th
dc.identifier.urihttps://repository.nida.ac.th/handle/662723737/5758th
dc.descriptionThesis (Ph.D. (Statistics))--National Institute of Development Administration, 2015th
dc.description.abstractIn this study, a test statistic used to select a multivariate linear regression model based on Mallows’s Cp with the same rationale as the SCp criterion from the system of equations Vichit Lorchirachoonkul and Jirawan Jitthavech (2012: 2386- 2394) proposed. The D statistic, which is the difference between the modified Cp statistics in the reduced model and in the full model, approximates to a standard normal distribution.th
dc.description.abstractThe modified C p statistic without the hypothesis testing, MC , and the proposed test statistic TD based on the percentage of selecting the model correctly were compared via a simulation study. Variable selection was carried out using backward elimination with five datasets consisting of 100 samples of size 200 and significance levels of 0.05 and 0.10, and the correlation between the equations was set at 0.3, 0.4, 0.5, 0.7, and 0.8, respectively. The multivariate linear regression full models consisted of two dependent variables, two relevant independent variables, and two irrelevant independent variables. In addition, the random disturbances were uncorrelated across observations in the same equation but contemporaneously correlated across equations. The results of the simulation study showed that the test statistic TD was able to select the model more often than the modified Cp criterion in all datasets, and, for both criteria, no under-fit models were selected.th
dc.description.provenanceMade available in DSpace on 2022-05-09T04:40:46Z (GMT). No. of bitstreams: 0 Previous issue date: 2015th
dc.format.extent185 leavesth
dc.format.mimetypeapplication/pdfth
dc.language.isoength
dc.publisherNational Institute of Development Administrationth
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.th
dc.subject.otherRegression analysisth
dc.subject.otherLinear models (Statistics)th
dc.titleA test statistic for selection of multivariate linear regression modelsth
dc.typeTextth
mods.genreDissertationth
mods.physicalLocationNational Institute of Development Administration. Library and Information Centerth
thesis.degree.nameDoctor of Philosophyth
thesis.degree.levelDoctoralth
thesis.degree.disciplineStatisticsth
thesis.degree.grantorNational Institute of Development Administrationth
thesis.degree.departmentSchool of Applied Statisticsth
dc.identifier.doi10.14457/NIDA.the.2015.57


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record