Font Size:
Functional principal component analysis of quantile curves
Last modified: 2017-05-22
Abstract
Literature on functional data analysis is mainly focused on estimation of individuals curves and characterization of average dynamics.
The idea underlying this proposal is to focus attention on other particular features of the distribution of the observed data,
moving from mean functions towards functional quantiles.
The motivating examples are functional data sets that are collections of high frequency data recorded along time.
As quantiles provide information on various aspects of a time series,
we propose a modelling framework for the joint estimation of functional quantiles, varying along time, and functional principal components,
summarizing some common dynamics shared by the functional quantiles.
The idea underlying this proposal is to focus attention on other particular features of the distribution of the observed data,
moving from mean functions towards functional quantiles.
The motivating examples are functional data sets that are collections of high frequency data recorded along time.
As quantiles provide information on various aspects of a time series,
we propose a modelling framework for the joint estimation of functional quantiles, varying along time, and functional principal components,
summarizing some common dynamics shared by the functional quantiles.