R help - Oct 2008 - Mclust problem with mclust1Dplot: Error in to - from : non-numeric argument to binary operator

Dear list members,

I am using Mclust in order to deconvolute a distribution that I
believe is a sum of two gaussians.

First I can make a model:
> my.data.model = Mclust(my.data, modelNames=c("E"), warn=T, G=1:3)
But then, when I try to plot the result, I get the following error:
> mclust1Dplot(my.data.model, parameters = my.data.model$parameters, what =
"density")
Error in to - from : non-numeric argument to binary operator

Also, I'd like to allow for each gaussian to have a different variance
(modelNmaes=c("V")) , but then I get another error message:
> my.data.model = Mclust(my.data, modelNames=c("V"), warn=T, G=1:3)
Warning messages:
1: In meV(data = data, z = z, prior = prior, control = control, warn = warn) :
  sigma-squared falls below threshold
2: In meV(data = data, z = z, prior = prior, control = control, warn = warn) :
  sigma-squared falls below threshold
3: In summary.mclustBIC(Bic, data, G = G, modelNames = modelNames) :
  best model occurs at the min or max # of components considered
4: In Mclust(my.data, modelNames = c("V"), warn = T, G = 1:3) :
  optimal number of clusters occurs at min choice

Many thanks in advance for your help,

Best wishes,

Emmanuel


If you would like to reproduce the above, the dataset is:

my.data=c( 0.0000,0.0052,0.0000,-0.2136,0.4625,0.6047,0.0000,0.7370,0.5059
,-0.8060,-1.0790,0.0000,-1.5397,-0.0720,-3.2180,-1.6980,0.0000,2.2845
,-1.0741,0.0000,0.1020,-0.6010,0.2210,-0.0120,1.0785,0.0000,-0.4536
,-0.1127,-0.2032,-0.0421,-1.6818,-0.9935,-2.2105,-0.7963,-0.1820,-2.0468
,0.6161,-1.7663,-0.6800,-2.1290,-0.0167,0.0000,0.0000,0.0000,0.5427
,-0.0170,0.0000,0.0000,-0.6576,0.9055,0.1409,-0.1409,0.0000,0.3730
,-0.1800,-1.3141,0.6786,-0.2480,-2.5110,-0.1340,0.3000,-1.7350,0.0000
,-0.5464,0.0000,-0.7513,-1.9056,-1.4823,-0.5376,-0.4516,-1.1391,0.0000
,-2.2560,1.3770,0.3390,-2.6023,-1.0880,-0.1444,0.0000,-0.1459,0.1740
,0.0000,0.3310,0.0749,1.0360,-0.8345,-0.6843,-3.5171,-1.9482,-0.4972
,-0.0130,-2.0290,-0.2812,0.0000,0.0000,-0.0164,0.0000,-1.9220,-1.5941
,-1.0840,0.0000,0.0459,-2.2121,-1.1485,-1.1485,0.0000,-0.4449,-0.5001
,0.3520,1.9980,-3.8385,1.7160,1.0020,-0.2250,-0.8265,-0.2032)

After playing with the data, I figured out what the problem is:
I've got many zeros in the dataset, which probably induces the
algorithm to determine a gaussian with variance=0.

If I remove the zeros it works, but then the decomposition is not as
it should be ....

Any idea on how to solve this would be great; is it possible to
somehow force the parameters (e.g variance) to be
greater than a particular threshold?

Thanks,

Emmanuel



2008/10/20 Emmanuel Levy <emmanuel.levy at
gmail.com>:
> Dear list members,
>
> I am using Mclust in order to deconvolute a distribution that I
> believe is a sum of two gaussians.
>
> First I can make a model:
>> my.data.model = Mclust(my.data, modelNames=c("E"), warn=T,
G=1:3)
>
> But then, when I try to plot the result, I get the following error:
>
>> mclust1Dplot(my.data.model, parameters = my.data.model$parameters, what
= "density")
> Error in to - from : non-numeric argument to binary operator
>
> Also, I'd like to allow for each gaussian to have a different variance
> (modelNmaes=c("V")) , but then I get another error message:
>
>> my.data.model = Mclust(my.data, modelNames=c("V"), warn=T,
G=1:3)
> Warning messages:
> 1: In meV(data = data, z = z, prior = prior, control = control, warn =
warn) :
>  sigma-squared falls below threshold
> 2: In meV(data = data, z = z, prior = prior, control = control, warn =
warn) :
>  sigma-squared falls below threshold
> 3: In summary.mclustBIC(Bic, data, G = G, modelNames = modelNames) :
>  best model occurs at the min or max # of components considered
> 4: In Mclust(my.data, modelNames = c("V"), warn = T, G = 1:3) :
>  optimal number of clusters occurs at min choice
>
> Many thanks in advance for your help,
>
> Best wishes,
>
> Emmanuel
>
>
> If you would like to reproduce the above, the dataset is:
>
> my.data=c( 0.0000,0.0052,0.0000,-0.2136,0.4625,0.6047,0.0000,0.7370,0.5059
> ,-0.8060,-1.0790,0.0000,-1.5397,-0.0720,-3.2180,-1.6980,0.0000,2.2845
> ,-1.0741,0.0000,0.1020,-0.6010,0.2210,-0.0120,1.0785,0.0000,-0.4536
> ,-0.1127,-0.2032,-0.0421,-1.6818,-0.9935,-2.2105,-0.7963,-0.1820,-2.0468
> ,0.6161,-1.7663,-0.6800,-2.1290,-0.0167,0.0000,0.0000,0.0000,0.5427
> ,-0.0170,0.0000,0.0000,-0.6576,0.9055,0.1409,-0.1409,0.0000,0.3730
> ,-0.1800,-1.3141,0.6786,-0.2480,-2.5110,-0.1340,0.3000,-1.7350,0.0000
> ,-0.5464,0.0000,-0.7513,-1.9056,-1.4823,-0.5376,-0.4516,-1.1391,0.0000
> ,-2.2560,1.3770,0.3390,-2.6023,-1.0880,-0.1444,0.0000,-0.1459,0.1740
> ,0.0000,0.3310,0.0749,1.0360,-0.8345,-0.6843,-3.5171,-1.9482,-0.4972
> ,-0.0130,-2.0290,-0.2812,0.0000,0.0000,-0.0164,0.0000,-1.9220,-1.5941
> ,-1.0840,0.0000,0.0459,-2.2121,-1.1485,-1.1485,0.0000,-0.4449,-0.5001
> ,0.3520,1.9980,-3.8385,1.7160,1.0020,-0.2250,-0.8265,-0.2032)
>