Testing for no effect via splines

Chin-Shang Li

Research output: Contribution to journalArticlepeer-review


A spline-based test statistic for a constant mean function is proposed based on the penalized residual sum-of-squares difference between the null model and a B-spline model in which the regression function is approximated with P-splines approach. When the number of knots is fixed, the limiting null distribution of the test statistic is shown to be the distribution of a linear combination of independent chi-squared random variables, each with one degree of freedom. A smoothing parameter is selected by setting a specified value equal to the expected value of the test statistic under the null hypothesis. Simulation experiments are conducted to study the proposed spline-based test statistic's finite-sample properties.

Original languageEnglish (US)
Pages (from-to)343-357
Number of pages15
JournalComputational Statistics
Issue number2
StatePublished - Jun 2012


  • B-spliness
  • P-splines
  • Penalized least-squares
  • Spline-based test

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Statistics, Probability and Uncertainty


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