One-Way High-Dimensional ANOVA

Tansheng Chen, Lukun Zheng and Jiancheng Jiang

Journal of Mathematics, 2023, vol. 2023, 1-11

Abstract: ANOVA is one of the most important tools in comparing the treatment means among different groups in repeated measurements. The classical F test is routinely used to test if the treatment means are the same across different groups. However, it is inefficient when the number of groups or dimension gets large. We propose a smoothing truncation test to deal with this problem. It is shown theoretically and empirically that the proposed test works regardless of the dimension. The limiting null and alternative distributions of our test statistic are established for fixed and diverging number of treatments. Simulations demonstrate superior performance of the proposed test over the F test in different settings.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/jmath/2023/9350523.pdf (application/pdf)
http://downloads.hindawi.com/journals/jmath/2023/9350523.xml (application/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:9350523

DOI: 10.1155/2023/9350523

Access Statistics for this article

More articles in Journal of Mathematics from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().