I'm sorry, I think I misunderstood your request, Mariela.

Mclust will give you the parameters for each mixture model (mean and variance). Here is what I meant:


library(mclust) # Mclust library for bimodal distributions

set.seed(314)

x <- c(rnorm(100), rnorm(100, 10,3))

hist(x, prob=T)

m <- Mclust(data=x)

summary(m, parameters=TRUE)



But now I suspect you mean the standard error for these estimates? If so, could you use bootstrap estimates? For example:

means.1 <- means.2 <- array()

for(i in 1:200) {

  sample <- sample(x, replace=T)

  m <- Mclust(data=sample)

  means.1[i] <- m$parameters$mean[1]

  means.2[i] <- m$parameters$mean[2]

  }

alarm() #So you can check e-mail, the internet, make coffee, etc. while it's running and hear when it finishes :)

# mean and standard error (approximated using 1 Std. dev. Of bootstrap resampling distribution)

list(mean1=mean(means.1), sd1=sd(means.1), mean2=mean(means.2), sd1=sd(means.2))

I'm not sure, if you have more than bimodal mixture models and small sample sizes, whether you would need to modify this to confirm that the parameters are for the proper mixed models. But it's something to consider. (Although we don't consider mixture models, you might find the following a useful reference. The online supplement has R example code. And you can get from my website, too.)

Kowalewski, M., and P. Novack-Gottshall. 2010. Resampling methods in paleontology. Pp. 19-54. In J. Alroy, and G. Hunt, eds. Quantitative Methods in Paleobiology. Short Courses in Paleontology 16. Paleontological Society and Paleontological Research Institute, Ithaca, NY.

You can control some EM parameters using emControl(), but I'm not as familiar with this. See ?mclust::emControl for details.

Best wishes,
Phil



On 5/15/2014 8:04 AM, Mariela Sued wrote:
I have tried to use mclust, but i could not get from is the sd of the parameter estimators.
I tried with Mclust and also with
In fact, I  would like to fix the initial value for the EM algorithm, and I was not able to do that-
Any suggestion?
I tried with Mclust and with densityMclust
best regards
Mariela


On Fri, May 9, 2014 at 11:30 AM, Novack-Gottshall, Philip M. <pnovack-gottshall@ben.edu<mailto:pnovack-gottshall@ben.edu>> wrote:
Have you tried taking a look at the mclust package? It's quite flexible,
and obtains these statistics.

Phil


On 5/9/2014 8:30 AM, Mariela Sued wrote:
> Hi!
> I am using normalmixEM to fit a  mixture of normal distributions.
> I dont see an estimation of the standard deviation of the parameters.
> Any idea?
> thanks in advance
> MAriela
>
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--
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 Phil Novack-Gottshall
 Associate Professor
 Department of Biological Sciences
 Benedictine University
 5700 College Road
 Lisle, IL 60532

 pnovack-gottshall@ben.edu<mailto:pnovack-gottshall@ben.edu>
 Phone: 630-829-6514
 Fax: 630-829-6547
 Office: 332 Birck Hall
 Lab: 107 Birck Hall
 http://www1.ben.edu/faculty/pnovack-gottshall
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~





--
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 Phil Novack-Gottshall
 Associate Professor
 Department of Biological Sciences
 Benedictine University
 5700 College Road
 Lisle, IL 60532

 pnovack-gottshall@ben.edu<mailto:pnovack-gottshall@ben.edu>
 Phone: 630-829-6514
 Fax: 630-829-6547
 Office: 332 Birck Hall
 Lab: 107 Birck Hall
 http://www1.ben.edu/faculty/pnovack-gottshall
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


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