Local quasi-likelihood with a parametric guide

Jianqing Fan, Yichao Wu, Yang Feng

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


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 languageEnglish (US)
Pages (from-to)4153-4183
Number of pages31
JournalAnnals of Statistics
Issue number6 B
StatePublished - Dec 2009
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


  • Generalized linear model
  • Local polynomial smoothing
  • Parametric guide
  • Quasi-likelihood method


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