R: Semi-Supervised Gaussian Mixture Model with a Missing-Data Mechanism

# Semi-Supervised Gaussian Mixture Model with a Missing-Data Mechanism

## Documentation for package ‘EMMIXSSL’ version 1.1.1

- DESCRIPTION file.

## Help Pages

Classifier_Bayes | Classifier based on Bayes rule
cov2vec | Transform a variance matrix into a vector
discriminant_beta | Discriminant function
EMMIXSSL | Fitting Gaussian mixture models
errorrate | Error rate of the Bayes rule for two-class Gaussian homoscedastic model
gastrodata | Gastrointestinal dataset
gastro_label_binary | Gastrointestinal binary labels
gastro_label_trinary | Gastrointestinal trinary labels
get_clusterprobs | Posterior probability
get_entropy | Shannon entropy
initialvalue | Initial values for ECM
list2par | Transfer a list into a vector
loglk_full | Full log-likelihood function
loglk_ig | Log likelihood for partially classified data with ingoring the missing mechanism
loglk_miss | Log likelihood function formed on the basis of the missing-label indicator
logsumexp | log summation of exponential function
makelabelmatrix | Label matrix
neg_objective_function | Negative objective function for EMMIXSSL
normalise_logprob | Normalize log-probability
par2list | Transfer a vector into a list
pro2vec | Transfer a probability vector into a vector
rlabel | Generation of a missing-data indicator
rmix | Normal mixture model generator.
vec2cov | Transform a vector into a matrix
vec2pro | Transfer an informative vector to a probability vector