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

A number of discrete time, finite population size models in geneticsdescribing the dynamics of allele frequencies are known to converge (subject tosuitable scaling) to a diffusion process in the infinite population limit,termed the Wright-Fisher diffusion. In this article we show that the diffusionis ergodic uniformly in the selection and mutation parameters, and that themeasures induced by the solution to the stochastic differential equation areuniformly locally asymptotically normal. Subsequently these two results areused to analyse the statistical properties of the Maximum Likelihood andBayesian estimators for the selection parameter, when both selection andmutation are acting on the population. In particular, it is shown that theseestimators are uniformly over compact sets consistent, display uniform in theselection parameter asymptotic normality and convergence of moments overcompact sets, and are asymptotically efficient for a suitable class of lossfunctions.

Convergence of Likelihood Ratios and Estimators for Selection in non-neutral Wright-Fisher Diffusions