Open Access
Translator Disclaimer
March, 1976 A Comparison of Chi-Square Goodness-of-Fit Tests Based on Approximate Bahadur Slope
M. C. Spruill
Ann. Statist. 4(2): 409-412 (March, 1976). DOI: 10.1214/aos/1176343418

Abstract

The Pearson-Fisher $\chi^2$ statistic is asymptotically chi-square under the null hypothesis with $M - m - 1$ degrees of freedom where $M =$ number of cells and $m =$ dimension of parameter. The Chernoff-Lehmann statistic is a weighted sum of chi-squares and the Kambhampati statistic is $\chi^2$ with $M - 1$ degrees of freedom. The approximate Bahadur slopes of the tests based on these statistics are computed. It is shown that the Kambhampati test always dominates the Chernoff-Lehmann and that no such dominance exists between the Pearson-Fisher test and Kambhampati test, or the Pearson-Fisher and Chernoff-Lehmann.

Citation

Download Citation

M. C. Spruill. "A Comparison of Chi-Square Goodness-of-Fit Tests Based on Approximate Bahadur Slope." Ann. Statist. 4 (2) 409 - 412, March, 1976. https://doi.org/10.1214/aos/1176343418

Information

Published: March, 1976
First available in Project Euclid: 12 April 2007

zbMATH: 0326.62036
MathSciNet: MR391380
Digital Object Identifier: 10.1214/aos/1176343418

Subjects:
Primary: 62G20
Secondary: 62F10

Keywords: Bahadur slope , Chi-square test

Rights: Copyright © 1976 Institute of Mathematical Statistics

JOURNAL ARTICLE
4 PAGES


SHARE
Vol.4 • No. 2 • March, 1976
Back to Top