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

The problem to establish not only the asymptotic distribution results forstatistical estimators but also the moment convergence of the estimators hasbeen recognized as an important issue in advanced theories of statistics. Oneof the main goals of this paper is to present a metod to derive the momentconvergence of $Z$-estimators as it has been done for $M$-estimators. Anothergoal of this paper is to develop a general, unified approach, based on somepartial estimation functions which we call "$Z$-process", to the change pointproblems for ergodic models as well as some models where the Fisher informationmatrix is random and inhomogeneous in time. Applications to some diffusionprocess models and Cox's regression model are also discussed.

Moment convergence of $Z$-estimators and $Z$-process method for change point problems