| em.fitdist | R Documentation |
The default em function
## S3 method for class 'fitdist'
em(
object,
latent = 2,
verbose = FALSE,
init.method = c("random", "kmeans", "hc"),
init.prob = NULL,
algo = c("em", "cem", "sem"),
max_iter = 500,
...
)
object |
the model used, e.g. 'lm', 'glm', 'gnm'. |
latent |
the number of latent classes. |
verbose |
'True' to print the process of convergence. |
init.method |
the initialization method used in the model. The default method is 'random'. 'kmeans' is K-means clustering. 'hc' is model-based agglomerative hierarchical clustering. |
init.prob |
the starting prior probabilities used in classification based method. |
algo |
the algorithm used in em: 'em' the default EM algorithm, the classification em 'cem', or the stochastic em 'sem'. |
max_iter |
the maximum iteration for em algorithm. |
... |
arguments used in the 'model'. |
An object of class 'em' is a list containing at least the following components:
models a list of models/objects whose class are determined by a model fitting from the previous step.
pi the prior probabilities.
latent number of the latent classes.
algorithm the algorithm used (could be either 'em', 'sem' or 'cem').
obs the number of observations.
post_pr the posterior probabilities.
concomitant a list of the concomitant model. It is empty if no concomitant model is used.
init.method the initialization method used.
call the matched call.
terms the codeterms object used.
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