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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We consider experiments for comparing treatments using units that are orderedlinearly over time or space within blocks. In addition to the block effect, weassume that a trend effect influences the response. The latter is modeled as asmooth component plus a random term that captures departures from the smoothtrend. The model is flexible enough to cover a variety of situations; forinstance, most of the effects may be either random or fixed. The informationmatrix for a design will be a function of several variance parameters. Whiledata will shed light on the values of these parameters, at the design stage,they are unlikely to be known, so we suggest a maximin approach, in which aminimal information matrix is maximized. We derive maximin universally optimaldesigns and study their robustness. These designs are based on semibalancedarrays. Special cases correspond to results available in the literature.

Optimal designs for mixed models in experiments based on ordered units