Assessing corrections to the weighted chi-squared test for dimension

Efstathia Bura, R. D. Cook

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

The weighted chi-squared test for dimension is an extension to the chi-squared test associated with sliced inverse regression as it lifts restrictive distributional assumptions on the predictors. Its usage requires the estimation of the mixture weights which may affect accuracy, and the computationally intensive calculation of percentiles of a mixture chi-squared distribution. The scaled and adjusted chi-squared corrections to the mixture chi-squared distribution have been proposed as alternatives to the weighted chi-squared test. A simulation study assessing power performance of the four tests indicates that the computationally simple adjusted chi-squared test could be used in place of the weighted chi-squared test, whereas the scaled chi-squared test performs much worse.

Original languageEnglish (US)
Pages (from-to)127-146
Number of pages20
JournalCommunications in Statistics Part B: Simulation and Computation
Volume32
Issue number1
DOIs
StatePublished - Feb 1 2003

Keywords

  • Dimension reduction
  • Regression
  • Sliced inverse regression

Fingerprint Dive into the research topics of 'Assessing corrections to the weighted chi-squared test for dimension'. Together they form a unique fingerprint.

Cite this