Show simple item record

dc.contributor.advisorGreenberg, Betsy S.en
dc.creatorKim, Yeoliben
dc.date.accessioned2010-11-30T21:53:15Zen
dc.date.accessioned2010-11-30T21:53:21Zen
dc.date.available2010-11-30T21:53:15Zen
dc.date.available2010-11-30T21:53:21Zen
dc.date.issued2010-05en
dc.date.submittedMay 2010en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2010-05-1459en
dc.descriptiontexten
dc.description.abstractThis research assesses the performance of over-dispersed Poisson regression model and negative binomial model with count data. It examines the association between price plan features of mobile phone services and the number of people who adopt the plan. Mobile service data is used to estimate the model with a sample of one million customers running from February 2006 to September 2009. Under three main categories, customer type, age, and handset price, we run the model based on price plan features. Estimates are derived from the maximum likelihood estimation (MLE) method. Root mean squared error (RMSE) is used to observe the statistical fits of all the regression models. Then, we construct four estimation and holdout samples, leaving out one, three, six, and twelve months. The estimation constitutes the in-sample (IS) and the holdout represents the out-sample (OS). By estimating the IS, we predict the OS. Root mean squared error of prediction (RMSEP) is checked to see how accurate the prediction is. Results generally suggest that academic year start (AYS), seasonality, duration of months since launch of price plan (DMLP), basic fees, rate with no discount (RND), free call minutes (FCM), free data (FD), free text messaging (FTM), free perk rating (FPR), and handset support all show significant effect. The significance occurs depending on the segment. The RMSE and RMSEP show that the over-dispersed Poisson model outperforms the negative binomial model. Further implications and limitations of the results are discussed.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectCount dataen
dc.subjectMobile telecommunication serviceen
dc.subjectPoisson modelen
dc.subjectNegative binomial modelen
dc.titleCount models : with applications to price plans in mobile telecommunication industryen
dc.date.updated2010-11-30T21:53:21Zen
dc.contributor.committeeMemberPeterson, Robert A.en
dc.description.departmentMathematicsen
dc.type.genrethesisen
thesis.degree.departmentMathematicsen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Statisticsen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record