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

Using an intrinsic approach, we study some properties of random fields whichappear as tail fields of regularly varying stationary random fields. The indexset is allowed to be a general locally compact Hausdorff Abelian group$\mathbb{G}$. The values are taken in a measurable cone, equipped with a pseudonorm. We first discuss some Palm formulas for the exceedance random measure$\xi$ associated with a stationary (measurable) random field $Y=(Y_s)_{s\in\mathbb{G}}$. It is important to allow the underlying stationary measure to be$\sigma$-finite. Then we proceed to a random field (defined on a probabilityspace) which is spectrally decomposable, in a sense which is motivated byextreme value theory. We characterize mass-stationarity of the exceedancerandom measure in terms of a suitable version of the classical Mecke equation.We also show that the associated stationary measure is homogeneous, that is atail measure. We then proceed with establishing and studying the spectralrepresentation of stationary tail measures and with characterizing a movingshift representation. Finally we discuss anchoring maps and the candidateextremal index.

Tail processes and tail measures: An approach via Palm calculus