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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we propose a simple and easy-to-implement Bayesian hypothesistest for the presence of an association, described by Kendall's \taucoefficient, between two variables measured on at least an ordinal scale. Owingto the absence of the likelihood functions for the data, we employ theasymptotic sampling distributions of the test statistic as the workinglikelihoods and then specify a truncated normal prior distribution on thenoncentrality parameter of the alternative hypothesis, which results in theBayes factor available in closed form in terms of the cumulative distributionfunction of the standard normal distribution. Investigating the asymptoticbehavior of the Bayes factor we find the conditions of the priors so that it isconsistent to whichever the hypothesis is true. Simulation studies and areal-data application are used to illustrate the effectiveness of the proposedBayes factor. It deserves mentioning that the proposed method can be easilycovered in undergraduate and graduate courses in nonparametric statistics withan emphasis on students' Bayesian thinking for data analysis.

A simple consistent Bayes factor for testing the Kendall rank correlation coefficient