A least squares estimation method for the linear learning model
The author presents a new method for estimating the parameters of the linear learning model. The procedure, essentially a least squares method, is easy to carry out and avoids certain difficulties of earlier estimation procedures. Applications to three different data sets are reported, as well as results from a goodness-of-fit test. A simulation study was carried out to validate the method. The outcomes are compared with those obtained from the minimum chi square estimation method. The results of the new method appear to be satisfactory.
|Keywords||CHI-square test, brand choice, consumer preferences, estimating theory, goodness-of-fit tests, least squares, linear models (statistics), marketing research, mathematical models, regression analysis, simulation methods, statistical hypothesis testing|
Wierenga, B.. (1978). A least squares estimation method for the linear learning model. Journal of Marketing Research, 15, 145–153. Retrieved from http://hdl.handle.net/1765/12556