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Sensitivity Analysis in Semiparametric Regression Models

In: Measurement and Multivariate Analysis

Author

Listed:
  • Wing-Kam Fung

    (University of Hong Kong, Department of Statistics and Actuarial Science)

  • Zhong-Yi Zhu

    (East China Normal University, Department of Statistics)

  • Bo-Cheng Wei

    (Southeast University, Department of Mathematics)

Abstract

Summary Research in semiparametric regression models has received attention in recent years. However, there is little work in the sensitivity analysis for such models. In this paper, we investigate the statistical diagnostics in semiparametric regression models. The case deletion influence diagnostics are constructed. An outlier diagnostic of the case deletion model is studied and it is shown to be equivalent to that of the mean-shift outlier model. The popular Cook’s distance is constructed which can be expressed in terms of the leverage measure and the residual. The proposed diagnostics are illustrated using a real data set.

Suggested Citation

  • Wing-Kam Fung & Zhong-Yi Zhu & Bo-Cheng Wei, 2002. "Sensitivity Analysis in Semiparametric Regression Models," Springer Books, in: Shizuhiko Nishisato & Yasumasa Baba & Hamparsum Bozdogan & Koji Kanefuji (ed.), Measurement and Multivariate Analysis, pages 233-240, Springer.
    • Handle: RePEc:spr:sprchp:978-4-431-65955-6_25
    DOI: 10.1007/978-4-431-65955-6_25
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