Interface | Description |
---|---|
BackwardElimination.Step | |
ForwardSelection.Step |
Class | Description |
---|---|
BackwardElimination |
Constructs a GLM model for a set of observations using the backward elimination method.
|
EliminationByAIC |
In each step, a factor is dropped if the resulting model has the least AIC, until no factor
removal can result in a model with AIC lower than the current AIC.
|
EliminationByZValue |
In each step, the factor with the least z-value is dropped, until all z-values are greater than
the critical value (given by the significance level).
|
ForwardSelection |
Constructs a GLM model for a set of observations using the forward selection method.
|
GLMModelSelection |
Given a set of observations {y, X}, we would like to construct a GLM to explain the data.
|
SelectionByAIC |
In each step, a factor is added if the resulting model has the highest AIC, until no factor
addition can result in a model with AIC higher than the current AIC.
|
SelectionByZValue |
In each step, the most significant factor is added, until all remaining factors are
insignificant.
|
Exception | Description |
---|---|
GLMModelSelection.ModelNotFound |
Throw a
ModelNotFound exception when fail to construct a model to
explain the data. |
Copyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.