Currently,working with partially observed functional data has attracted a greatly increas-ing attention,since there are ......

We propose a flexible robust functional regression model,using various heavy-tailed processes,including a Student t-proc......

Faced with new types of data,statisticians require models that can handle complex random objects.This motivates the deve......

We develop a functional conditional autoregressive(CAR)model for spatially correlated data for which functions are colle......

Gene set enrichment analyses(GSEA)are powerful inferential methods widely used in genomic research to identify significa......

By using advanced motion capture systems,human movement data can be collected densely over time and functional data anal......

In this paper,we consider composite quantile regression for partial functional linear re-gression model with polynomial ......