FLXMCmvnorm {flexmix} | R Documentation |
This is a demo driver for flexmix
implementing
model-based clustering of Gaussian data.
FLXMCmvnorm(formula = . ~ ., diagonal = TRUE)
formula |
A formula which is interpreted relative to the formula
specified in the call to flexmix using
update.formula . Only the left-hand side (response) of
the formula is used. Default is to use the original
flexmix model
formula. |
diagonal |
If TRUE , then the covariance matrix of the
components is restricted to diagonal matrices. |
This is mostly meant as a demo for FlexMix driver programming, you should also look at package mclust for real applications.
FLXMCmvnorm
returns an object of class FLXMC
.
Friedrich Leisch and Bettina Gruen
Friedrich Leisch. FlexMix: A general framework for finite mixture models and latent class regression in R. Journal of Statistical Software, 11(8), 2004. http://www.jstatsoft.org/v11/i08/
data("Nclus") require("MASS") eqscplot(Nclus) ## This model is wrong (one component has a non-diagonal cov matrix) ex1 <- flexmix(Nclus~1, k=4, model=FLXMCmvnorm()) print(ex1) plotEll(ex1, Nclus) ## True model, wrong number of components ex2 <- flexmix(Nclus~1, k=6, model=FLXMCmvnorm(diag=FALSE)) print(ex2) plotEll(ex2, Nclus) ## Get parameters of first component parameters(ex2, component=1) ## Have a look at the posterior probabilies of 10 random observations ok <- sample(1:nrow(Nclus), 10) p <- posterior(ex2)[ok,] p ## The following two should be the same max.col(p) clusters(ex2)[ok]