On estimation of the effect lag of predictors and prediction in functional linear model

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We propose a functional linear model to predict a response using multiple functional and longitudinal predictors and to estimate the effect lags of predictors. The coefficient functions are written as the expansion of a basis system (e.g. functional principal components, splines), and the coefficients of the fixed basis functions are estimated via optimizing a penalization criterion. Then time lags are determined by simultaneously searching on a prior grid mesh based on minimization of prediction error criterion. Moreover, mathematical properties of the estimated parameters and predicted responses are studied and performance of the method is evaluated by extensive simulations.