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 test procedure based on the LASSO methodology totest the global null hypothesis of no dependence between a response variableand $p$ predictors, where $n$ observations with $n < p$ are available. Theproposed procedure is similar to the F-test for a linear model, which evaluatessignificance based on the ratio of explained to unexplained variance. However,the F-test is not suitable for models where $p \geq n$. This limitation is dueto the fact that when $p \geq n$, the unexplained variance is zero and thus theF-statistic can no longer be calculated. In contrast, the proposed extension ofthe LASSO methodology overcomes this limitation by using the number of non-zerocoefficients in the LASSO model as a test statistic after suitably specifyingthe regularization parameter. The method allows reliable analysis ofhigh-dimensional datasets with as few as $n = 40$ observations. The performanceof the method is tested by means of a power study.

LASSO extension: using the number of non-zero coefficients to test the global model hypothesis