JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Local Influence of the Quasi-likelihood Estimators in Generalized Linear Models
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Local Influence of the Quasi-likelihood Estimators in Generalized Linear Models
Jung, Kang-Mo;
  PDF(new window)
 Abstract
We present a diagnostic method for the quasi-likelihood estimators in generalized linear models. Since these estimators can be usually obtained by iteratively reweighted least squares which are well known to be very sensitive to unusual data, a diagnostic step is indispensable to analysis of data. We extend the local influence approach based on the maximum likelihood function to that on the quasi-likelihood function. Under several perturbation schemes local influence diagnostics are derived. An illustrative example is given and we compare the results provided by local influence and deletion.
 Keywords
Cook`s distance;diagnostics;generalized linear models;local influence;maximum likelihood estimator;quasi-likelihood estimator;
 Language
English
 Cited by
1.
Multiple Deletions in Logistic Regression Models,;

Communications for Statistical Applications and Methods, 2009. vol.16. 2, pp.309-315 crossref(new window)
 References
1.
Allison, T. and Cicchetti, D. (1976). Sleep in mammals: Ecological and constitutional correlates. Science, 194, 732-734 crossref(new window)

2.
Cook, R. D. (1986). Assessment of local influence. Journal of the Royal Statistical Society, Ser. B, 48, 133-169

3.
Davis, C. S. (2002). Statistical Methods for the Analysis of Repeated Measurements, Springer-Verlag, New York

4.
Dobson, A. J. (2002). An Introduction to Generalized Linear Models. 2nd ed., Chapman & Hall/CRC

5.
Emerson, J. D., Hoaglin, D. C. and Kempthorne, P. J. (1984). Leverage in least squares additive-plus-multiplicative fits for two-way tables. Journal of the American Statistical Association, 79, 329-335 crossref(new window)

6.
Faraway, J. J. (2006). Extending the Linear Model with R. Chapman & Hall/CRC

7.
Lesaffre, E. and Verbeke, G. (1998). Local influence in linear mixed models. Biometrics, 54, 570-582 crossref(new window)

8.
McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models. 2nd ed., Chapman & Hall/CRC

9.
Nelder, J. A. and Wedderburn, R. W. M. (1972). Generalized linear models, Journal of the Royal Statistical Society, A, 135, 370-384 crossref(new window)

10.
Suarez Rancel, M. M. and Gonzalez Sierra, M. A. (2001). Regression diagnostic using local influence: a review. Communications in Statistics - Theory and Methods, 30, 799-813 crossref(new window)

11.
Thomas, W. and Cook, R. D. (1989). Assessing influence on regression coefficients in generalized linear models. Biometrika, 76, 741-749 crossref(new window)

12.
Wedderburn, R. W. M. (1974). Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method. Biometrika, 61, 439-447

13.
Zhu, H. and Zhang, H. (2004). A diagnostic procedure based on local influence, Biometrika, 91, 579-589 crossref(new window)