English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper analyzes whether procedures for multiple comparison derived in Hyodo et al. (2012) work for an unbalanced case and under non-normality. We focus on pairwise multiple comparisons and comparison with a control among mean vectors, and show that the asymptotic properties of these procedures remain valid in unbalanced high-dimensional setting. We also numerically justify that the derived procedures are robust under non-normality, i.e., the coverage probability of these procedures can be controlled with or without the assumption of normality of the data.

journal of the japanese society of computational statistics

&lt;b&gt;MULTIPLE COMPARISON PROCEDURES &lt;/b&gt;&lt;b&gt;FOR HIGH-DIMENSIONAL DATA AND THEIR ROBUSTNESS &lt;/b&gt;&lt;b&gt;UNDER NON-NORMALITY &lt;/b&gt;