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

Let YT = (Yt )t∈[0,T] be a real ergodic diffusion process which drift depends on an unkown parameter . Our aim is to estimate θ 0 from a discrete observation of the process YT , (Ykδ )k=0,n , for a fixed and small δ , as T = nδ goes to infinity. For that purpose, we adapt the Generalized Method of Moments (see Hansen) to the anticipative and approximate discrete-time trapezoidal scheme, and then to Simpson's. Under some general assumptions, the trapezoidal scheme (respectively Simpson's scheme) provides an estimation of θ 0 with a bias of order δ 2 (resp. δ 4 ). Moreover, this estimator is asymptotically normal. These results generalize Bergstrom's [1], which were obtained for a Gaussian diffusion process, which drift is linear in θ .

Schémas de discrétisation anticipatifs et estimation du paramètre de dérive d'une diffusion