Forecasting binary longitudinal data by a functional PC-ARIMA model

Abstract

Abstract. The purpose of this paper is to forecast the time evolution of a binary response variable from an associated continuous time series observed only at dis-crete time points that usually are unequally spaced. In order to solve this problem we are going to use a functional logit model based on functional principal com-ponent analysis of the predictor time series that takes into account its continuous nature, close to classical ARIMA modelling of the associated discrete time series of principal components