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

A process  X  is observed continuously in time; it behaves like Brownian motion with drift, which changes from zero to a known constant ϑ&gt;0 at some time τ that is not directly observable. It is important to detect this change when it happens, and we attempt to do so by selecting a stopping rule  T  *  that minimizes the “expected miss”  E | T −τ| over all stopping rules  T . Assuming that τ has an exponential distribution with known parameter λ&gt;0 and is independent of the driving Brownian motion, we show that the optimal rule  T  *  is to declare that the change has occurred, at the first time  t  for which

A note on Bayesian detection of change-points with an expected miss criterion