MAXIMUM LIKELIHOOD ESTIMATION IN LINEAR LEARNING MODELS
成果类型：
Article
署名作者：
PRUSCHA, H
署名单位：
Max Planck Society
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/63.3.537
发表日期：
1976
页码：
537542
关键词：
摘要：
An extension of the Markov model with only a few additional parameters is the linear learning model, as introduced by Bush et Mosteller. 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 et Mosteller, are included, as well as comparisons between the linear learning model and the Markov model.