mcvis | R Documentation |
Multi-collinearity Visualization
mcvis(
X,
sampling_method = "bootstrap",
standardise_method = "studentise",
times = 1000L,
k = 10L
)
X |
A matrix of regressors (without intercept terms). |
sampling_method |
The resampling method for the data. Currently supports 'bootstrap' or 'cv' (cross-validation). |
standardise_method |
The standardisation method for the data. Currently supports 'euclidean' (default, centered by mean and divide by Euclidiean length) and 'studentise' (centred by mean and divide by standard deviation) and 'none' (no standardisation) |
times |
Number of resampling runs we perform. Default is set to 1000. |
k |
Number of partitions in averaging the MC-index. Default is set to 10. |
A list of outputs:
t_square:The t^2 statistics for the regression between the VIFs and the tau's.
MC:The MC-indices
col_names:Column names (export for plotting purposes)
Chen Lin, Kevin Wang, Samuel Mueller
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 = X)
mcvis_result
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