Abstract
Generalized linear models and the quasi-likelihood method extend the ordinary regression models to accommodate more general conditional distributions of the response. Nonparametric methods need no explicit parametric specification, and the resulting model is completely determined by the data themselves. However, nonparametric estimation schemes generally have a slower convergence rate such as the local polynomial smoothing estimation of nonparametric generalized linear models studied in Fan, Heckman and Wand [J. Amer. Statist. Assoc. 90.
Original language | English (US) |
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Pages (from-to) | 4153-4183 |
Number of pages | 31 |
Journal | Annals of Statistics |
Volume | 37 |
Issue number | 6 B |
DOIs | |
State | Published - Dec 2009 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
Keywords
- Generalized linear model
- Local polynomial smoothing
- Parametric guide
- Quasi-likelihood method