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

The upper bound inequality for variance of weighted sum of correlated randomvariables is derived according to Cauchy-Schwarz's inequality, while theweights are non-negative with sum of 1. We also give a novel proof withpositive semidefinite matrix method. And the variance inequality of sum ofcorrelated random variable with general weights is also obtained. Then, thevariance inequalities are applied to the Chebyshev's inequality and sufficientcondition of weak law of large numbers (WLLN) for sum of correlated randomvariables .

Inequality for Variance of Weighted Sum of Correlated Random Variables and WLLN