bootclus {evclust} | R Documentation |
Generating a credal partition by bootstraping Gaussian Mixture Models
Description
bootclus
generates a credal partition by bootstrapping Gaussian Mixture Models.
Usage
bootclus(
x,
conf = 0.9,
B = 500,
param = list(G = NULL),
type = "pairs",
Omega = FALSE
)
Arguments
x |
attribute matrix or data frame of size (n,p). |
conf |
confidence level (default: 0.90). |
B |
number of bootstrap samples (default=500) |
param |
list of arguments passed to function |
type |
Type of focal sets ("simple": |
Omega |
Logical. If TRUE, |
Details
This function uses the mclust
package to generate and bootstrap the mixture models.
Value
A list with the following components:
- clus
An object of class '
Mclust
' returned byMclust
.- Clus
An object of class '
credpart
' providing the output credal partition.- CI
An array of dimension (2,n,n) containing the confidence intervals on pairwise probabilities.
- BelPl
An array of dimension (2,n,n) containing the pairwise Bel-Pl intervals.
- Time
A matrix of size (3,5) containing the computing time as returned by function
proctime
for (1) the parameter estimation and bootstrap, (2) the computation fo the quantiles on pairwise probabilities, and (3) the computation of the credal partition.
References
T. Denoeux. Calibrated model-based evidential clustering using bootstrapping. Information Sciences, Vol. 528, pages 17-45, 2020.
See Also
Examples
## Example with the Faithful geyser data
## Not run:
data("faithful")
X<-faithful
param=list(G=3)
res.faithful<-bootclus(X,conf=0.90,B=100,param=param)
## Plot the results
plot(res.faithful$Clus,X)
## End(Not run)