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

Usual estimation methods for the parameters of extreme values distributionemploy only a few values, wasting a lot of information. More precisely, in thecase of the Gumbel distribution, only the block maxima values are used. In thiswork, we propose a method to seize all the available information in order toincrease the accuracy of the estimations. This intent can be achieved by takingadvantage of the existing relationship between the parameters of the baselinedistribution, which generates data from the full sample space, and the ones forthe limit Gumbel distribution. In this way, an informative prior distributioncan be obtained. Different statistical tests are used to compare the behaviourof our method with the standard one, showing that the proposed method performswell when dealing with very shortened available data. The empiricaleffectiveness of the approach is demonstrated through a simulation study and acase study. Reduction in the credible interval width and enhancement inparameter location show that the results with improved prior adapt to veryshortened data better than standard method does.

An improved method for the estimation of the Gumbel distribution parameters