[R] Extracting individual parameter estimates from mmlcr

[Rben]

I am new to mmlcr and am working on a latent class mixture model attempting
to identify
the trajectory and number of classes that best describes my data. I am able
to find model 
parameters such as degrees of freedom, loglikelihood, and BIC.

For example, here is a cubic 3-class model I am using.

mmlcr1 <- mmlcr(outer = ~ 1 | ID, components = list(list(formula = Score ~
poly(wave,3), 
 class = "cnormlong", min = 1, max = 4)), data = datlong, n.groups = 3)

In this model I can find these parameters as follows:

mmlcrl$df
mmlcr1$loglikelihood
mmlcr1$BIC

And I can identify individual parameter estimates such as posterior
probabilities of
belonging to specific classes, specific data points, corresponding fitted
and residual values 
as follows:

#posterior probability of belonging to class 1
summary.mmlcr(mmlcr1)[7]$post.prob$PostProb1

#first data value
summary.mmlcr(mmlcr1)$components[[1]]$data[1,]$PDS

#first fitted value
summary.mmlcr(mmlcr1)$components[[1]]$fitted[1]

#first residual value
summary.mmlcr(mmlcr1)$components[[1]]$residual[1]

BUT I am unable to figure out how to extract individual parameter estimates
such as intercepts, linear/quadratic/cubic slopes of my model. Is this found
in a similar way or can it be computed. If it can be computed, does anyone
know
how this is done in the context of this program?

Thanks for any help.
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