Other Data Modeling Techniques

There are other techniques besides least squares fitting to model data and develop curve fit relations. Other data modeling techniques include inverse-Hessian, steepest descent, and Levenberg-Marquadt methods that are used to map data to general nonlinear functions. Monte Carlo algorithms use statistical techniques to model data according to a probability distribution.

We won't implement any of these data modeling techniques in this chapter, but if you were to do so you would follow a similar procedure as was used to implement the least squares curve fit method. First, you would determine if the algorithm could be implemented as a generic class library and, if so, divide the analysis into generic and problem-specific parts . You would then most likely implement the data modeling technique as a public static method accepting any problem-specific data as arguments to the method.