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

The Adaptive Multilevel Splitting algorithm is a very powerful and versatileiterative method to estimate the probability of rare events, based on aninteracting particle systems. In an other article, in a so-called idealizedsetting, the authors prove that some associated estimators are unbiased, foreach value of the size n of the systems of replicas and of resampling number k.Here we go beyond and prove these estimator's asymptotic normality when h goesto infinity, for any fixed value of k. The main ingredient is the asymptoticanalysis of a functional equation on an appropriate characteristic function.Some numerical simulations illustrate the convergence to rely on Gaussianconfidence intervals.

Central Limit Theorem for Adaptative Multilevel Splitting Estimators in an Idealized Setting