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On local influence for elliptical linear models

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Abstract

The local influence method plays an important role in regression diagnostics and sensitivity analysis. To implement it, we need the Delta matrix for the underlying scheme of perturbations, in addition to the observed information matrix under the postulated model. Galea, Paula and Bolfarine (1997) has recently given the observed information matrix and the Delta matrix for a scheme of scale perturbations and has assessed of local influence for elliptical linear regression models. In the present paper, we consider the same elliptical linear regression models. We study the schemes of scale, predictor and response perturbations, and obtain their corresponding Delta matrices, respectively. To illustrate the methodology for assessment of local influence for these schemes and the implementation of the obtained results, we give an example.

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References

  • Aiktson, A.C. (1985)Plots, Transformations, and Regression, Clarendon, Oxford.

    Google Scholar 

  • Chatterjee, S. and Hadi, A. S. (1988)Sensitivity Analysis in Linear Regression, Wiley, New York.

    MATH  Google Scholar 

  • Cook, R.D. (1986) Assessment of local influence (with discussion),J. R. Statist. Soc. B, 48, 133–169.

    MATH  Google Scholar 

  • Cook, R.D. (1997) Local influence, inEncyclopedia of Statist. Sciences, Kotz, S., Read, C.B. and Banks, D.L. eds., Wiley, New York, Update Vol. 1, 380–385.

    Google Scholar 

  • Davison, A.C. and Tsai, C.-L. (1992) Regression model diagnostics,Int. Statist. Rev., 60, 337–353.

    Article  MATH  Google Scholar 

  • Fang, K.T. and Anderson, T.W. (1990)Statistical Inferences in Elliptical Contoured and Related Distributions, Allerton, New York.

    Google Scholar 

  • Fang, K.T. and Zhang, Y. (1990)Generalized Multivariate Analysis, Science Press, Beijing/Springer, Berlin.

    MATH  Google Scholar 

  • Farebrother, R.W. (1992) Relative local influence and the condition number,Commun. Statist.-Simulation. Comput., 21, 707–710.

    Article  Google Scholar 

  • Farebrother, R.W. (1999)Fitting Linear Relationships: A History of the Calculus of Observations 1750–1900, Springer, New York.

    MATH  Google Scholar 

  • Galea, M., Paula, G.A. and Bolfarine, H. (1997) Local influence in elliptical linear regression models,The Statistician, 46(1), 71–79.

    Google Scholar 

  • Jung, K.M., Kim, M.G. and Kim, B.C. (1997) Second order local influence in linear discriminant analysis,J. Japan. Soc. Comp. Statist., 10(1), 1–11.

    MathSciNet  MATH  Google Scholar 

  • Kollo, T. and Neudecker, H. (1993) Asymptotics of eigenvalues and unit-length eigenvectors of sample variance and correlation matrices,J. Multivar. Anal., 47, 283–300. Corrigendum, 51, 210.

    Article  MathSciNet  MATH  Google Scholar 

  • Kollo, T. and Neudecker, H. (1997) Asymptotics of Pearson-Hotelling principalcomponent vectors of sample variance and correlation matrices.Behaviormetrika, 24(1), 51–69.

    Article  Google Scholar 

  • Magnus, J.R. and Neudecker, H. (1999)Matrix Differential Calculus with Applications in Statistics and Econometrics, second edition, Wiley, Chichester.

    MATH  Google Scholar 

  • Peña, D. (1997) Combining information in statistical modeling,The Am. Statistician, 51(4), 326–332.

    Article  Google Scholar 

  • Ruppert, D. and Carroll, R.J. (1980) Trimmed least squares estimation in the linear model,J. Am. Statist. Ass., 75, 828–838.

    Article  MathSciNet  MATH  Google Scholar 

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Liu, S. On local influence for elliptical linear models. Statistical Papers 41, 211–224 (2000). https://doi.org/10.1007/BF02926104

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  • DOI: https://doi.org/10.1007/BF02926104

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