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/

Zendy Plus

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

Zendy Tools

Zendy Open

Empirical distributions have their in-sample maxima as natural censoring. Welook at the "hidden tail", that is, the part of the distribution in excess ofthe maximum for a sample size of $n$. Using extreme value theory, we examinethe properties of the hidden tail and calculate its moments of order $p$. Themethod is useful in showing how large a bias one can expect, for a given $n$,between the visible in-sample mean and the true statistical mean (or highermoments), which is considerable for $\alpha$ close to 1. Among otherproperties, we note that the "hidden" moment of order $0$, that is, theexceedance probability for power law distributions, follows an exponentialdistribution and has for expectation $\frac{1}{n}$ regardless of theparametrization of the scale and tail index.

What You See and What You Don't See: The Hidden Moments of a Probability Distribution