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/

Zendy Plus

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

Zendy Tools

Zendy Open

Local Fr\'echet regression is a nonparametric regression method for metricspace valued responses and Euclidean predictors, which can be utilized toobtain estimates of smooth trajectories taking values in general metric spacesfrom noisy metric space valued random objects. We derive uniform rates ofconvergence, which so far have eluded theoretical analysis of this method, forboth fixed and random target trajectories, where we utilize tools fromempirical processes. These results are shown to be widely applicable in metricspace valued data analysis. In addition to simulations, we provide twopertinent examples where these results are important: The consistent estimationof the location of properly defined extrema in metric space valuedtrajectories, which we illustrate with the problem of locating the age ofminimum brain connectivity as obtained from fMRI data; Time warping for metricspace valued trajectories, illustrated with yearly age-at-death distributionsfor different countries.

Uniform convergence of local Fr\'echet regression, with applications to locating extrema and time warping for metric space valued trajectories