Recursive Estimation for Time Series Following Generalized Linear Models

Abstract

A recursive estimation method for time series models following generalized linear models is studied in two ways. The estimation procedure, suitably modified, gives rise to a stochastic approximation scheme. We use the modified estimation procedure to illustrate a connection between control theory and generalized linear models by employing a logistic regression model.