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

We consider functional data where an underlying smooth curve is composed notjust with errors, but also with irregular spikes. We propose an approach that,combining regularized spline smoothing and an Expectation-Maximizationalgorithm, allows one to both identify spikes and estimate the smoothcomponent. Imposing some assumptions on the error distribution, we proveconsistency of EM estimates. Next, we demonstrate the performance of ourproposal on finite samples and its robustness to assumptions violations throughsimulations. Finally, we apply our proposal to data on the annual heatwavesindex in the US and on weekly electricity consumption in Ireland. In bothdatasets, we are able to characterize underlying smooth trends and to pinpointirregular/extreme behaviors.

smoothEM: a new approach for the simultaneous assessment of smooth patterns and spikes