Uses the EM algorithm for estimating a latent class model.
apollo_beta |
Named numeric vector. Names and values for parameters.
|
apollo_fixed |
Character vector. Names (as defined in apollo_beta ) of parameters whose value should not
change during estimation.
|
apollo_probabilities |
Function. Returns probabilities of the model to be estimated. Must receive three arguments:
-
apollo_beta : Named numeric vector. Names and values of model parameters.
-
apollo_inputs : List containing options of the model. See apollo_validateInputs.
-
functionality : Character. Can be either
"components" , "conditionals" , "estimate" (default), "gradient" , "output" , "prediction" , "preprocess" , "raw" , "report" , "shares_LL" , "validate" or "zero_LL" .
|
apollo_inputs |
List grouping most common inputs. Created by function apollo_validateInputs.
|
lcEM_settings |
List. Options controlling the EM process.
-
EMmaxIterations: Numeric. Maximum number of iterations of the EM algorithm before
stopping. Default is 100.
-
postEM: Numeric scalar. Determines the tasks performed by this function
after the EM algorithm has converged. Can take values 0 , 1
or 2 only. If value is 0 , only the EM algorithm will be
performed, and the results will be a model object without a covariance
matrix (i.e. estimates only). If value is 1 , after the EM
algorithm, the covariance matrix of the model will be calculated as well,
and the result will be a model object with a covariance matrix. If value
is 2 , after the EM algorithm, the estimated parameter values will
be used as starting value for a maximum likelihood estimation process,
which will render a model object with a covariance matrix. Performing
maximum likelihood estimation after the EM algorithm is useful, as there
may be room for further improvement. Default is 2 .
-
silent: Boolean. If TRUE, no information is printed to the console during
estimation. Default is FALSE.
-
stoppingCriterion: Numeric. Convergence criterion. The EM process will stop when
improvements in the log-likelihood fall below this value.
Default is 10^-5.
|
estimate_settings |
List. Options controlling the estimation process within each EM iteration. See
apollo_estimate for details.
|
This function uses the EM algorithm for estimating a Latent Class model. It is only suitable for models without
continuous mixing. All parameters need to vary across classes and need to be included in the apollo_lcPars
function which is used by apollo_lcEM
.