A goodness-of-fit test for variable-adjusted models

Chuanlong Xie, Lixing Zhu*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

25 Citations (Scopus)


This research provides a projection-based test to check parametric single-index regression structure in variable-adjusted models. An adaptive-to-model strategy is employed, which makes the proposed test work better on the significance level maintenance and more powerful than existing tests. With mild conditions, the proposed test asymptotically behaves like a test that is for classical regression setup without distortion errors in observations. Numerical studies with simulated and real data are conducted to examine the performance of the test in finite sample scenarios.

Original languageEnglish
Pages (from-to)27-48
Number of pages22
JournalComputational Statistics and Data Analysis
Publication statusPublished - Oct 2019

Scopus Subject Areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

User-Defined Keywords

  • Adaptive-to-model test
  • Dimension reduction
  • Distortion errors
  • Variable-adjusted model


Dive into the research topics of 'A goodness-of-fit test for variable-adjusted models'. Together they form a unique fingerprint.

Cite this