Lack-of-fit tests for generalized linear models via splines

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Abstract

Cubic B-splines are used to estimate the nonparametric component of a semiparametric generalized linear model. A penalized log-likelihood ratio test statistic is constructed for the null hypothesis of the linearity of the nonparametric function. When the number of knots is fixed, its limiting null distribution is the distribution of a linear combination of independent chi-squared random variables, each with one df. The smoothing parameter is determined by giving a specified value for its asymptotically expected value under the null hypothesis. A simulation study is conducted to evaluate its power performance; a real-life dataset is used to illustrate its practical use.

Original languageEnglish (US)
Pages (from-to)4240-4250
Number of pages11
JournalCommunications in Statistics - Theory and Methods
Volume41
Issue number23
DOIs
StatePublished - Dec 1 2012

Keywords

  • B-spline
  • Generalized linear model
  • Generalized partially linear model
  • Penalized log-likelihood ratio test
  • Semiparametric generalized linear model

ASJC Scopus subject areas

  • Statistics and Probability

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