alt_mcvis {mcvis} | R Documentation |
Multi-collinearity Visualization plots
Description
Multi-collinearity Visualization plots
Multi-collinearity Visualization plots
Multi-collinearity Visualization plots
Usage
alt_mcvis(mcvis_result, eig_max = 1L, var_max = ncol(mcvis_result$MC))
ggplot_mcvis(
mcvis_result,
eig_max = 1L,
var_max = ncol(mcvis_result$MC),
label_dodge = FALSE
)
igraph_mcvis(mcvis_result, eig_max = 1L, var_max = ncol(mcvis_result$MC))
## S3 method for class 'mcvis'
plot(
x,
type = c("ggplot", "igraph", "alt"),
eig_max = 1L,
var_max = ncol(x$MC),
label_dodge = FALSE,
...
)
Arguments
mcvis_result |
Output of the mcvis function |
eig_max |
The maximum number of eigenvalues to be displayed on the plot. |
var_max |
The maximum number of variables to be displayed on the plot. |
label_dodge |
If variable names are too long, it might be helpful to dodge the labelling. Default to FALSE. |
x |
Output of the mcvis function |
type |
Plotting mcvis result using "igraph" or "ggplot". Default to "ggplot". |
... |
additional arguments (currently unused) |
Value
A mcvis visualization plot
Author(s)
Chen Lin, Kevin Wang, Samuel Mueller
Examples
set.seed(1)
p = 10
n = 100
X = matrix(rnorm(n*p), ncol = p)
X[,1] = X[,2] + rnorm(n, 0, 0.1)
mcvis_result = mcvis(X)
plot(mcvis_result)
plot(mcvis_result, type = "igraph")
plot(mcvis_result, type = "alt")
[Package mcvis version 1.0.8 Index]