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Local influence analysis for penalized Gaussian likelihood estimation in partially linear single-index models
| Content Provider | Semantic Scholar |
|---|---|
| Author | Zhu, Zhongyi Wang, Jinglong |
| Copyright Year | 2009 |
| Abstract | Single-index model is a potentially tool for multivariate nonparametric regression, generalizes both the generalized linear models(GLM) and the missing-link function problem in GLM. In this paper, we extend Cook’s local influence analysis to the penalized Gaussian likelihood estimator based on P-spline for the partially linear single-index model. Some influence measures, based on the minor perturbation of the model, are derived for the penalized least squares estimation. An illustrative example is also presented. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ism.ac.jp/editsec/aism/pdf/061_4_0905.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | B-spline Function problem Generalized linear model Least squares Normal Statistical Distribution Single-index model Smoothing spline Spline (mathematics) |
| Content Type | Text |
| Resource Type | Article |
