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

This paper addresses sensitivity analysis for dynamic models, linkingdependent inputs to observed outputs. The usual method to estimate Sobolindices are based on the independence of input variables. We present a methodto overpass this constraint when inputs are Gaussian processes of highdimension in a time related framework. Our proposition leads to ageneralization of Sobol indices when inputs are both dependant and dynamic. Themethod of estimation is a modification of the Pick and Freeze simulationscheme. First we study the general Gaussian cases and secondly we detail thecase of stationary models. We then apply the results to an example of heatexchanges inside a building.

Pick and freeze estimation of sensitivity indices for models with dependent and dynamic input processes