com.numericalmethod.suanshu.stats.regression.linear.modelselection
Class Forward

java.lang.Object
  com.numericalmethod.suanshu.stats.regression.linear.modelselection.Forward

public class Forward
extends java.lang.Object

To construct a GLM model for a set of observations using the forward selection method, we iteratively add a significant factor to the model, one at a time. This repeats until all remaining factors are insignificant.

Nested Class Summary

static class

SingleFactorSelection.ModelNotFound We throw a ModelNotFound exception when we fail to construct a model to explain the data.

Field Summary

double	criticalValue a critical value A factor is considered significant if its z-value is bigger than some critical value.
GlmProblem	problem the GLM problem to be solved

Constructor Summary

Forward(GlmProblem problem, double significance)
Construct automatically a GLM model using the forward selection method.

Method Summary

GeneralizedLinearModel

model() Get the constructed model.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

problem

public final GlmProblem problem

the GLM problem to be solved

criticalValue

public final double criticalValue

a critical value

A factor is considered significant if its z-value is bigger than some critical value. We add the significant factors to the model.

Constructor Detail

Forward

public Forward(GlmProblem problem,
               double significance)

Construct automatically a GLM model using the forward selection method.

Parameters:

problem - a GLM problem

significance - a critical value to determine whether a factor is significant (to be included in the model)

Method Detail

model

public GeneralizedLinearModel model()

Get the constructed model.

Returns:

a GLM model