The StepwiseRegression type exposes the following members.
Constructors
Name | Description | |
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StepwiseRegression | Overloaded. |
Methods
Name | Description | |
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Compute |
Builds the multiple linear regression models using forward selection,
backward selection, or stepwise selection.
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Equals | (Inherited from Object.) | |
Finalize |
Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
(Inherited from Object.) | |
GetHashCode |
Serves as a hash function for a particular type.
(Inherited from Object.) | |
GetType |
Gets the Type of the current instance.
(Inherited from Object.) | |
MemberwiseClone |
Creates a shallow copy of the current Object.
(Inherited from Object.) | |
SetMeans |
Sets the means of the variables.
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ToString | (Inherited from Object.) |
Properties
Name | Description | |
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ANOVA |
An analysis of variance table and related statistics.
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CoefficientTTests |
The student-t test statistics for the regression
coefficients.
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CoefficientVIF |
The variance inflation factors for the final model in this
invocation.
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CovariancesSwept |
Results after cov has been swept for the columns
corresponding to the variables in the model.
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Force |
Forces independent variables into the model based on their level
assigned from Levels.
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History |
The stepwise regression history for the independent variables.
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Intercept |
Returns the intercept.
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Levels |
The levels of priority for variables entering and leaving the
regression.
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Method |
Specifies the stepwise selection method, forward, backward, or
stepwise Regression.
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PValueIn |
Defines the largest p-value for variables entering the model.
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PValueOut |
Defines the smallest p-value for removing variables.
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Swept |
An array containing information indicating whether or not a
particular variable is in the model.
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Tolerance |
The tolerance used to detect linear dependence among the independent
variables.
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