On local influence for elliptical linear models

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

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

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

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.

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

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

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

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

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

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

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.

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.

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

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

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

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