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 |