Nonparametric Predictive Model for Sparse and Irregular
Longitudinal Data
Description
The proposed method aims at predicting the longitudinal mean response trajectory by a
kernel-based estimator. The kernel estimator is constructed by imposing weights based on
subject-wise similarity on L2 metric space between predictor trajectories as well as time proximity.
Users could also perform variable selections to derive functional predictors with predictive significance
by the proposed multiplicative model with multivariate Gaussian kernels.