R help - Sep 2011 - mclust: modelName="E" vs modelName="V"

Hi,

I'm trying to use the library mclust for gaussian mixture on a numeric
vector. The function Mclust(data,G=3) is working fine but the fitting is not
optimal and is using modelNames="E". When I'm trying
Mclust(data,G=3,modelName="V") I have the following message:

Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else
ans[orderedNames] :
  argument is of length zero
In addition: Warning message:
In pickBIC(object[as.character(G), modelNames, drop = FALSE], k = 3) :
  none of the selected models could be fitted


Using variable variance would fit my data better, any idea how to do it?

Thanks a lot. 

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This normally happens if the algorithm gets caught in a solution where one 
of the components has variance converging to zero.

One way of dealing with this is the use of a prior that penalises too 
small variances. This works through the prior argument of Mclust (the 
defaultPrior should do the trick but I currently don't have the time to 
figure out again how to do this precisely; I have done it before with 
success).

Another option is to have a look at the flexmix package.

Best regards,
Christian

On Sun, 4 Sep 2011, Nico902 wrote:
> Hi,
>
> I'm trying to use the library mclust for gaussian mixture on a numeric
> vector. The function Mclust(data,G=3) is working fine but the fitting is
not
> optimal and is using modelNames="E". When I'm trying
> Mclust(data,G=3,modelName="V") I have the following message:
>
> Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else
ans[orderedNames] :
>  argument is of length zero
> In addition: Warning message:
> In pickBIC(object[as.character(G), modelNames, drop = FALSE], k = 3) :
>  none of the selected models could be fitted
>
>
> Using variable variance would fit my data better, any idea how to do it?
>
> Thanks a lot.
>
> --
> View this message in context:
http://r.789695.n4.nabble.com/mclust-modelName-E-vs-modelName-V-tp3789167p3789167.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
*** --- ***
Christian Hennig
University College London, Department of Statistical Science
Gower St., London WC1E 6BT, phone +44 207 679 1698
chrish at stats.ucl.ac.uk, www.homepages.ucl.ac.uk/~ucakche

Hi,

Thanks a lot for your answer. I effectively was able to get rid of this
message by doing:
> resClust <-
>
Mclust(data,G=3,modelName="V",prior=priorControl(scale=c(1.44,0.81,0.49)));

However, I would like to be able to retrieve the variances I defined in the
result. I found:
> resClust$parameters
$Vinv
NULL

$pro
[1] 0.5502496 0.1986852 0.2510652

$mean
            1             2             3 
-2.8390006980 -0.0003267873  3.1072574619 

$variance
$variance$modelName
[1] "V"

$variance$d
[1] 1

$variance$G
[1] 3

$variance$sigmasq
[1] 0.840267666 0.009466821 1.510263146

$variance$scale
[1] 0.840267666 0.009466821 1.510263146


I do not manage to get where the sigmasq is coming from. I tried to sqrt or
square the sigmasq but it does not correspond to what I defined. I found
nothing in the manual. If I am missing something obvious or if somebody has
the solution it will help me a lot. I want to retrieve those values
automatically to plot the different curves of the fitting and to be sure
this is doing what I want.

Thank you very much again.

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