vifmiqo: Eliminate Multicollinearity
In egfried/Rvifmiqo: Eliminate Multicollinearity in Multiple Regression
Description
Usage
Arguments
Value
Description
This function loads data in two pieces, X and y. Then it selects the subset
of variables that minimize multicollinearity using a mixed-integer optimization
framework.
Usage
1
vifmiqo(X, y, alpha = 5)
Arguments
X
Dataframe containing potential covariates and their values
y
Dataframe with output values corresponding to X
alpha
Optional- standard constraint > 1
Value
A list containing the optimal subset of parameters ("") and the corresponding
total number selected ("S"), R^2 for linear regression ("Rsq"), and VIF value ("VIF_max")
egfried/Rvifmiqo documentation built on Dec. 23, 2021, 10:23 p.m.
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Description Usage Arguments Value
Description
This function loads data in two pieces, X and y. Then it selects the subset of variables that minimize multicollinearity using a mixed-integer optimization framework.
Usage
1 | vifmiqo(X, y, alpha = 5)
|
Arguments
X |
Dataframe containing potential covariates and their values |
y |
Dataframe with output values corresponding to X |
alpha |
Optional- standard constraint > 1 |
Value
A list containing the optimal subset of parameters ("") and the corresponding total number selected ("S"), R^2 for linear regression ("Rsq"), and VIF value ("VIF_max")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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