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

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

## Documentation for package ‘gmmsslm’ version 1.1.6

- DESCRIPTION file

## Help Pages

bayesclassifier | Bayes' rule of allocation
bootstrap_gmmsslm | Bootstrap Analysis for gmmsslm
cov2vec | Transform a variance matrix into a vector
discriminant_beta | Discriminant function
erate | Error rate of the Bayes rule for a g-class Gaussian mixture model
errorrate | Error rate of the Bayes rule for two-class Gaussian homoscedastic model
gastro_data | Gastrointestinal dataset
get_clusterprobs | Posterior probability
get_entropy | Shannon entropy
gmmsslm | Fitting Gaussian mixture model to a complete classified dataset or an incomplete classified dataset with/without the missing-data mechanism.
gmmsslmFit-class | gmmsslmFit Class
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 gmmssl
normalise_logprob | Normalize log-probability
par2list | Transfer a vector into a list
paraextract | Extract parameter list from gmmsslmFit objects
paraextract-method | Extract parameter list from gmmsslmFit objects
plot_missingness | Plot Missingness Mechanism and Boxplot
predict | Predict unclassified label
predict-method | Predict unclassified label
pro2vec | Transfer a probability vector into a vector
rlabel | Generation of a missing-data indicator
rmix | Normal mixture model generator.
summary | Summary method for gmmsslmFit objects
summary-method | Summary method for gmmsslmFit objects
vec2cov | Transform a vector into a matrix
vec2pro | Transfer an informative vector to a probability vector