RVIF {rvif}

RVIF calculation

Description

This function provides the values of the Redefined Variance Inflation Factor (RVIF) and the the percentage of near multicollinearity due to each independent variable.

Usage

RVIF(X, l_u=TRUE, l=40, intercept=TRUE, graf=TRUE)

Arguments

X

A numeric design matrix that should contain more than one regressor.

l_u

A logical value that indicates if the variables in the design matrix X are transformed to have unit length. By default l_u=TRUE.

l

A real number that indicates the lower limit of the vertical axis of the scatter plot between the Variance Inflation Factor (VIF) and the Coefficient of Variation (CV). By default l=40.

intercept

A logical value that indicates if the design matrix X have intercept. By default intercept=TRUE.

graf

A logical value that indicates if the scatter plot between the VIF and CV is represented by using CV_VIF function. By default graf=TRUE.

Details

The Redefined Variation Inflation Factor (RVIF) is able to detect both kind of multicollinearity: the essential (near-linear relationship between at least two independent variables excluding the intercept) an non-essential (near-linear relationship between the intercept and at least one of the remaining independent variables). This measure also quantifies the percentage of near multicollinearity due to each independent variable.

Value

RVIF

Redefined Variance Inflation Factor of each independent variable.

%

Percentage of near multicollinearity due to each independent variable.

Graph

Scatter plot of VIF and the CV.

Author(s)

R. Salmerón ([e-mail]) and C. García ([e-mail]).

References

R. Salmerón, C. García, and J. García. Variance inflation factor and condition number in multiple linear regression. Journal of Statistical Computation and Simulation, 88:2365-2384, 2018.

R. Salmerón, A. Rodríguez, and C. García. Diagnosis and quantification of the non-essential collinearity. Computational Statistics, 35:647-666, 2020.

A redefined VIF by Salmerón, R., García, C.B, García, J. (working paper).

See Also

CV_VIF

Examples

library(multiColl)
set.seed(2022)
obs = 100
cte = rep(1, obs)
x2 = rnorm(obs, 5, 0.01)
x3 = rnorm(obs, 5, 10)
x4 = x3 + rnorm(obs, 5, 1)
x5 = rnorm(obs, -1, 30)
x = cbind(cte, x2, x3, x4, x5)
RVIF(x)