mergeparameters | R Documentation |
Re-computes pointwise posterior probabilities, mean and covariance matrix for a mixture component obtained by merging two mixture components in a Gaussian mixture.
mergeparameters(xdata, j1, j2, probs, muarray,Sigmaarray, z)
xdata |
data (something that can be coerced into a matrix). |
j1 |
integer. Number of first mixture component to be merged. |
j2 |
integer. Number of second mixture component to be merged. |
probs |
vector of component proportions (for all components; should sum up to one). |
muarray |
matrix of component means (rows). |
Sigmaarray |
array of component covariance matrices (third dimension refers to component number). |
z |
matrix of observation- (row-)wise posterior probabilities of belonging to the components (columns). |
List with components
probs |
see above; sum of probabilities for original components
|
muarray |
see above; weighted mean of means of component
|
Sigmaarray |
see above; weighted covariance matrix handled as above. |
z |
see above; original entries for columns |
Christian Hennig christian.hennig@unibo.it https://www.unibo.it/sitoweb/christian.hennig/en/
Hennig, C. (2010) Methods for merging Gaussian mixture components, Advances in Data Analysis and Classification, 4, 3-34.
options(digits=3)
set.seed(98765)
require(mclust)
iriss <- iris[sample(150,20),-5]
irisBIC <- mclustBIC(iriss)
siris <- summary(irisBIC,iriss)
probs <- siris$parameters$pro
muarray <- siris$parameters$mean
Sigmaarray <- siris$parameters$variance$sigma
z <- siris$z
mpi <- mergeparameters(iriss,1,2,probs,muarray,Sigmaarray,z)
mpi$probs
mpi$muarray
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