AIC                     Compute the Akaike Information Criterion (AIC)
                        of a Gaussian mixture model or graphical model
BIC                     Compute the Bayesian Information Criterion
                        (BIC) of a Gaussian mixture model or graphical
                        model
add_arcs                Add arcs to a Gaussian mixture graphical model
add_nodes               Add nodes to a Gaussian mixture graphical model
add_var                 Add variables to a Gaussian mixture model
aggregation             Aggregate particles to obtain inferred values
conditional             Conditionalize a Gaussian mixture model
data_air                Beijing air quality dataset
data_body               NHANES body composition dataset
density                 Compute densities of a Gaussian mixture model
ellipses                Display the mixture components of a Gaussian
                        mixture model
em                      Estimate the parameters of a Gaussian mixture
                        model
expectation             Compute expectations of a Gaussian mixture
                        model
filtering               Perform filtering inference in a Gaussian
                        mixture dynamic Bayesian network
gmbn                    Create a Gaussian mixture Bayesian network
gmbn_body               Gaussian mixture Bayesian network learned from
                        the NHANES body composition dataset
gmdbn                   Create a Gaussian mixture dynamic Bayesian
                        network
gmdbn_air               Gaussian mixture dynamic Bayesian network
                        learned from the Beijing air quality dataset
gmgm-package            Gaussian mixture graphical model learning and
                        inference
gmm                     Create a Gaussian mixture model
gmm_body                Gaussian mixture model learned from the NHANES
                        body composition dataset
inference               Perform inference in a Gaussian mixture
                        Bayesian network
logLik                  Compute the log-likelihood of a Gaussian
                        mixture model or graphical model
merge_comp              Merge mixture components of a Gaussian mixture
                        model
network                 Display the graphical structure of a Gaussian
                        mixture Bayesian network
param_em                Learn the parameters of a Gaussian mixture
                        graphical model with incomplete data
param_learn             Learn the parameters of a Gaussian mixture
                        graphical model
particles               Initialize particles to perform inference in a
                        Gaussian mixture graphical model
prediction              Perform predictive inference in a Gaussian
                        mixture dynamic Bayesian network
propagation             Propagate particles forward in time
relevant                Extract the minimal sub-Gaussian mixture
                        graphical model required to infer a subset of
                        nodes
remove_arcs             Remove arcs from a Gaussian mixture graphical
                        model
remove_nodes            Remove nodes from a Gaussian mixture graphical
                        model
remove_var              Remove variables from a Gaussian mixture model
rename_nodes            Rename nodes of a Gaussian mixture graphical
                        model
rename_var              Rename variables of a Gaussian mixture model
reorder                 Reorder the variables and the mixture
                        components of a Gaussian mixture model
sampling                Sample a Gaussian mixture model
smem                    Select the number of mixture components and
                        estimate the parameters of a Gaussian mixture
                        model
smoothing               Perform smoothing inference in a Gaussian
                        mixture dynamic Bayesian network
split_comp              Split a mixture component of a Gaussian mixture
                        model
stepwise                Select the explanatory variables, the number of
                        mixture components and estimate the parameters
                        of a conditional Gaussian mixture model
struct_em               Learn the structure and the parameters of a
                        Gaussian mixture graphical model with
                        incomplete data
struct_learn            Learn the structure and the parameters of a
                        Gaussian mixture graphical model
structure               Provide the graphical structure of a Gaussian
                        mixture graphical model
summary                 Summarize a Gaussian mixture model or graphical
                        model
