Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-28T22:05:31.774Z Has data issue: false hasContentIssue false

ON SMOOTH TESTS FOR THE EQUALITY OF DISTRIBUTIONS

Published online by Cambridge University Press:  12 January 2021

Xiaojun Song
Affiliation:
Peking University
Zhijie Xiao*
Affiliation:
Boston College
*
Address correspondence to Department of Economics, Boston College, Chestnut Hill, MA 02467, USA; e-mail: [email protected]. Xiao thanks Boston College for research support.

Abstract

This note re-investigates the smooth tests for the equality of distributions introduced by Bera et al. (2013, Econometric Theory 29, 419–446) and provides a modified smooth test which works for the general case with two sample sizes m and n. Asymptotic properties of the proposed test statistic under both the null and the alternative hypothesis are studied.

Type
MISCELLANEA
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

We thank two referees, Yoon-Jae Whang (the Co-Editor), Peter Phillips, Norbert Henze, Anil Bera, Aurobindo Ghosh, and Tong Yang for their very helpful comments. Song acknowledges the financial support from China's National Key Research Special Program Grants 2016YFC0207705, the National Natural Science Foundation of China (Grant No. 71532001, 71973005), and Key Laboratory of Mathematical Economics and Quantitative Finance (Peking University), Ministry of Education, China.

References

REFERENCES

Bera, A.K. & Ghosh, A. (2002) Neyman’s smooth test and its applications in Econometrics. In Ullah, A., Wan, A., Chaturvedi, A., & Dekker, M. (eds.), Handbook of Applied Econometrics and Statistical Inference, pp. 177230, New York: Marcel Dekker.Google Scholar
Bera, A.K., Ghosh, A., & Xiao, Z. (2013) A smooth test for the equality of distributions. Econometric Theory 29, 419446.CrossRefGoogle Scholar
Ducharme, G.R. & Ledwina, T. (2003) Efficient and adaptive nonparametric tests for the two-sample problem. Annals of Statistics 31, 20362058.CrossRefGoogle Scholar
Janic-Wroblewska, A. & Ledwina, T. (2000) Data driven rank test for two sample problem. Scandinavian Journal of Statistics 27, 281297.CrossRefGoogle Scholar
Lee, A.J. (1990). U-Statistics: Theory and Practice. Marcel Dekker.Google Scholar
Lehmann, E.L. (1975) Nonparametrics: Statistical Methods Based on Ranks. Holden-Day.Google Scholar
Neyman, J. (1937) “Smooth test” for goodness of fit. Skandinaviske Aktuarietidskrift 20, 150199.Google Scholar
Shorack, G.R. & Wellner, J. (1986) Empirical Processes with Applications to Statistics. Wiley.Google Scholar
Thas, O. (2010) Comparing Distributions. Springer.CrossRefGoogle Scholar
Wylupek, G. (2010) Data-driven k-sample tests. Technometrics 52, 107123.CrossRefGoogle Scholar
Zhou, W.-X., Zheng, C., & Zhang, Z. (2017) Two-sample smooth tests for the equality of distributions. Bernoulli 23, 951989.CrossRefGoogle Scholar