6.
Process or Product Monitoring and Control
6.4. Introduction to Time Series Analysis 6.4.4. Univariate Time Series Models


Use Software  Estimating the parameters for the BoxJenkins models is a quite complicated nonlinear estimation problem. For this reason, the parameter estimation should be left to a high quality software program that fits BoxJenkins models. Fortunately, many commerical statistical software programs now fit BoxJenkins models.  
Approaches 
The main approaches to fitting BoxJenkins models are
nonlinear least squares
and maximum likelihood estimation.
Maximum likelihood estimation is generally the preferred technique. The likelihood equations for the full BoxJenkins model are complicated and are not included here. See (Brockwell and Davis, 1991) for the mathematical details. 

Model Estimation Example  The Negiz case study shows an example of the BoxJenkins modelfitting. 