vsccmanly {vscc} | R Documentation |
Variable Selection for Skewed Clustering and Classification
Description
Performs variable selection under a clustering framework. Accounts for mixtures of non-Gaussian distributions via the ManlyTransform (via 'ManlyMix').
Usage
vsccmanly(x, G=2:9, numstart=100, selection="backward",forcereduction=FALSE,
initstart="k-means", seedval=2354)
Arguments
x |
Data frame or matrix to perform variable selection on |
G |
Vector for the number of groups to consider during initialization and/or post-selection analysis. Default is 2-9. |
numstart |
Number of random starts. |
selection |
Forward or backward transformation parameter selection. User may also choose to fit a full Manly mixture (options are 'forward', 'backward', or 'none'). |
forcereduction |
Logical indicating if the full data set should be considered (FALSE) when selecting the ‘best’ variable subset via total model uncertainty. |
initstart |
Method for initial starting values (options are 'k-means' or 'hierarchical'). |
seedval |
Value of seed, used for k-means initialization. |
Value
selected |
A list containing the subsets of variables selected for each relation. Each set is numbered according to the number in the exponential of the relationship. For instance, |
wss |
The within-group variance associated with each variable from the full data set. |
topselected |
The best variable subset according to the total model uncertainty. |
initialrun |
Results from the initial model, prior to variable selection; an object of class |
bestmodel |
Results from the best model on the selected variable subset; an object of class |
variables |
Variables used to fit the final model. |
chosenrelation |
Numeric indication of the relationship chosen according to total model uncertainty. The number corresponds to exponent in the relationship: for instance, a value of '4' suggests the quartic relationship. If the value |
uncertainty |
Total model uncertainty associated with the best relationship. |
allmodelfit |
List containing the results ( |
Author(s)
Jeffrey L. Andrews, Mackenzie R. Neal, Paul D. McNicholas
References
See citation("vscc")
for the variable selection references.
See Also
Examples
## Not run:
data(ais)
X=ais[,3:13]
aisfor=vsccmanly(as.data.frame(scale(X)),G=2:9,selection = "forward", forcereduction = TRUE,
initstart = "k-means",seedval=2354)
aisfor$variables #Show selected variables
table(ais[,1], aisfor$bestmodel$id) #Clustering results on reduced data set
## End(Not run)