We propose nonparametric methods for functional linear regression which are designed for sparse longitudinal data, where both the predictor and response are functions of a covariate such as time.

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

In regression problems alternative criteria of "best fit" to least squares are least absolute deviations and least maximum deviations. In this paper it is noted that linear programming techniques may ...