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

In many cases, the reseachers face the problem how to design the experiment which deal with the real situation. This is because the designs on literature do not suit the case. To solve the problem, optimal design can be an alternative. There are two approaches on optimal design: an analytical and a computational approach. An algorithm in the computational approach is needed to find an optimal design. The optimal design is a part of experimental design which seeks the design based on a certain criterion. The criterion which focuses on presicion of prediction variance is I-optimality criterion. Limited literatures address the I- optimality criterion for ordinal response. Most of literatures address to developing algorithms of other optimality criteria for General Linear Model. As the response is ordinal, hence the ordinal response belongs to non-linear model.

Algorithms for i-optimal designs for ordinal response: a literature approach