Local Influence Analysis for Penalized Gaussian Likelihood Estimators in Partially Linear Models
Partially linear models are extensions of linear models to include a non-parametric function of some covariate. They have been found to be useful in both cross-sectional and longitudinal studies. This paper provides a convenient means to extend Cook's local influence analysis to the penalized Gaussian likelihood estimator that uses a smoothing spline as a solution to its non-parametric component. Insight is also provided into the interplay of the influence or leverage measures between the linear and the non-parametric components in the model. The diagnostics are applied to a mouthwash data set and a longitudinal hormone study with informative results. Copyright 2003 Board of the Foundation of the Scandinavian Journal of Statistics..
Year of publication: |
2003
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Authors: | Zhu, Zhong-Yi ; He, Xuming ; Fung, Wing-Kam |
Published in: |
Scandinavian Journal of Statistics. - Danish Society for Theoretical Statistics, ISSN 0303-6898. - Vol. 30.2003, 4, p. 767-780
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Publisher: |
Danish Society for Theoretical Statistics Finnish Statistical Society Norwegian Statistical Association Swedish Statistical Association |
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