Model checking in Tobit regression model via nonparametric smoothing

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dc.contributor.author Liu, Shan
dc.date.accessioned 2012-05-04T13:04:50Z
dc.date.available 2012-05-04T13:04:50Z
dc.date.issued 2012-05-04
dc.identifier.uri http://hdl.handle.net/2097/13790
dc.description.abstract A nonparametric lack-of-fit test is proposed to check the adequacy of the presumed parametric form for the regression function in Tobit regression models by applying Zheng's device with weighted residuals. It is shown that testing the null hypothesis for the standard Tobit regression models is equivalent to test a new null hypothesis of the classic regression models. An optimal weight function is identified to maximize the local power of the test. The test statistic proposed is shown to be asymptotically normal under null hypothesis, consistent against some fixed alternatives, and has nontrivial power for some local nonparametric power for some local nonparametric alternatives. The finite sample performance of the proposed test is assessed by Monte-Carlo simulations. An empirical study is conducted based on the data of University of Michigan Panel Study of Income Dynamics for the year 1975. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Tobit regression model en_US
dc.subject Zheng's test en_US
dc.subject Consistency and Local Power en_US
dc.title Model checking in Tobit regression model via nonparametric smoothing en_US
dc.type Report en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Statistics en_US
dc.description.advisor Weixing Song en_US
dc.subject.umi Statistics (0463) en_US
dc.date.published 2012 en_US
dc.date.graduationmonth May en_US


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