Matrix of misclassification probabilities between mixture components
Matrix of misclassification probabilities in a mixture distribution between two mixture components from estimated posterior probabilities regardless of component parameters, see Hennig (2010).
zmisclassification.matrix(z,pro=NULL,clustering=NULL,
ipairs="all",symmetric=TRUE,
stat="max")z |
matrix of posterior probabilities for observations (rows) to belong to mixture components (columns), so entries need to sum up to 1 for each row. |
pro |
vector of component proportions, need to sum up to
1. Computed from |
clustering |
vector of integers giving the estimated mixture
components for every observation. Computed from |
ipairs |
|
symmetric |
logical. If |
stat |
|
A matrix with the (symmetrised, if required) misclassification
probabilities between each pair of mixture components. If
symmetric=FALSE, matrix entry [i,j] is the estimated
probability that an observation generated by component
j is classified to component i by maximum a posteriori rule.
Hennig, C. (2010) Methods for merging Gaussian mixture components, Advances in Data Analysis and Classification, 4, 3-34.
set.seed(12345) m <- rpois(20,lambda=5) dim(m) <- c(5,4) m <- m/apply(m,1,sum) round(zmisclassification.matrix(m,symmetric=FALSE),digits=2)
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