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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

A great deal of inference in statistics is based on making the approximationthat a statistic is normally distributed. The error in doing so is generally$O(n^{-1/2})$ and can be very considerable when the distribution is heavilybiased or skew. This note shows how one may reduce this error to$O(n^{-(j+1)/2})$, where $j$ is a given integer. The case considered is whenthe statistic is the mean of the sample values from a continuous one-parameterdistribution, after the sample has undergone an initial transformation.

Accurate inference for a one parameter distribution based on the mean of a transformed sample