Estimation of Constant Gain Learning Models

This paper provides a concise primer on the estimation of constant gain learning models. One practical concern in the estimation procedure is the initialization of the learning parameters. The popular approach in the literature relies on a training sample to estimate these quantities. We also consider the alternative, that of estimating these alongside the other model parameters. As we show with the aid of both simulated data and real data examples, the estimates are comparable using either approach.