| bicE {mclust} | R Documentation |
Compute the BIC (Bayesian Information Criterion) for a parameterized mixture model given the loglikelihood, the dimension of the data, and number of mixture components in the model.
bicE(loglik, n, G, equalPro, noise = FALSE, ...) bicV(loglik, n, G, equalPro, noise = FALSE, ...) bicEII(loglik, n, d, G, equalPro, noise = FALSE, ...) bicVII(loglik, n, d, G, equalPro, noise = FALSE, ...) bicEEI(loglik, n, d, G, equalPro, noise = FALSE, ...) bicVEI(loglik, n, d, G, equalPro, noise = FALSE, ...) bicEVI(loglik, n, d, G, equalPro, noise = FALSE, ...) bicVVI(loglik, n, d, G, equalPro, noise = FALSE, ...) bicEEE(loglik, n, d, G, equalPro, noise = FALSE, ...) bicEEV(loglik, n, d, G, equalPro, noise = FALSE, ...) bicVEV(loglik, n, d, G, equalPro, noise = FALSE, ...) bicVVV(loglik, n, d, G, equalPro, noise = FALSE, ...)
loglik |
The loglikelihood for a data set with respect to the MVN mixture model. |
n |
The number of observations in the data used to compute
loglik.
|
d |
The dimension of the data used to compute loglik.
|
G |
The number of components in the MVN mixture model used to compute
loglik.
|
equalPro |
A logical variable indicating whether or not the components in the
model are assumed to be present in equal proportion. The default is
.Mclust\$equalPro.
|
noise |
A logical variable indicating whether or not the model includes and optional Poisson noise component. The default is to assume that the model does not include a noise component. |
... |
Catch unused arguments from a do.call call.
|
The BIC or Bayesian Information Criterion for the MVN mixture model and data set corresponding to the input arguments.
C. Fraley and A. E. Raftery (2002a). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611:631. See http://www.stat.washington.edu/mclust.
C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington. See http://www.stat.washington.edu/mclust.
bic,
EMclust,
estepE,
mclustOptions,
do.call
## To run an example, see man page for bic
## Not run:
data(iris)
irisMatrix <- as.matrix(iris[,1:4])
irisClass <- iris[,5]
n <- nrow(irisMatrix)
d <- ncol(irisMatrix)
G <- 3
emEst <- meVVI(data=irisMatrix, unmap(irisClass))
names(emEst)
bicVVI(loglik=emEst$loglik, n=n, d=d, G=G)
do.call("bicVVI", emEst) ## alternative call
## End(Not run)