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Journal of Statistical Theory and Practice

, Volume 9, Issue 3, pp 479–488 | Cite as

Approximately Distribution-Free Diagnostic Tests for Regressions With Survival Data

  • Simos G. Meintanis
  • Efthymios Tsionas
Article

Abstract

We consider a linear regression model in which responses are in the form of log-duration while the corresponding error is modeled by means of a nonstandard distribution. This lifetime model is estimated by maximum likelihood and the estimates are used as basis for omnibus goodness-of-fit tests for the error distribution. In particular, we suggest a specific transformation such that when it is applied to the residuals, the corresponding test of fit becomes nonparametric, in the sense that the null distribution of the test statistic is the same regardless of the specific distribution being tested or of the values of the parameters involved in the regression model (such as regression parameters or other parameters figuring in the error distribution). The proposed procedure is applied to regressions involving the Birnbaum-Saunders, the extended Weibull, and the generalized Weibull distributions.

Keywords

Goodness-of-fit test Lifetime data Maximum likelihood Transformation to normality 

AMS Subject Classification

62G10 62G20 62P05 

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Copyright information

© Grace Scientific Publishing 2015

Authors and Affiliations

  1. 1.Department of EconomicsNational and Kapodistrian University of AthensAthensGreece
  2. 2.Unit for Business Mathematics and InformaticsNorth-West UniversityPotchefstroomSouth Africa
  3. 3.Department of EconomicsAthens University of Economics and BusinessAthensGreece

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