A profile-type smoothed score function for a varying coefficient partially linear model

Gaorong Li, Sanying Feng, Heng Peng*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

19 Citations (Scopus)


The varying coefficient partially linear model is considered in this paper. When the plug-in estimators of coefficient functions are used, the resulting smoothing score function becomes biased due to the slow convergence rate of nonparametric estimations. To reduce the bias of the resulting smoothing score function, a profile-type smoothed score function is proposed to draw inferences on the parameters of interest without using the quasi-likelihood framework, the least favorable curve, a higher order kernel or under-smoothing. The resulting profile-type statistic is still asymptotically Chi-squared under some regularity conditions. The results are then used to construct confidence regions for the parameters of interest. A simulation study is carried out to assess the performance of the proposed method and to compare it with the profile least-squares method. A real dataset is analyzed for illustration.

Original languageEnglish
Pages (from-to)372-385
Number of pages14
JournalJournal of Multivariate Analysis
Issue number2
Publication statusPublished - Feb 2011

Scopus Subject Areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Confidence region
  • Curse of dimensionality
  • Local likelihood
  • Profile-type smoothed score function
  • Varying coefficient partially linear model


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