Maximum Likelihood Estimation in Linear Learning Models

Abstract

An extension of the Markov model with only a few additional parameters is the linear learning model, as introduced by Bush & Mosteller (1955). To help its application in biological research an iterative procedure for calculating the maximum likelihood estimates of the unknown parameters is presented. Numerical examples, some of which have already been treated by Bush & Mosteller, are included, as well as comparisons between the linear learning model and the Markov model.