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 offer a complete methodology for sufficient dimensionreduction called the test function (TF). TF provides a new family of methodsfor the estimation of the central subspace (CS) based on the introduction of anonlinear transformation of the response. Theoretical background of TF isdeveloped under weaker conditions than the existing methods. By consideringorder 1 and 2 conditional moments of the predictor given the response, wedivide TF in two classes. In each class we provide conditions that guarantee anexhaustive estimation of the CS. Besides, the optimal members are calculatedvia the minimization of the asymptotic mean squared error deriving from thedistance between the CS and its estimate. This leads us to two plug-in methodswhich are evaluated with several simulations.

Test function: A new approach for covering the central subspace