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Hi,

I need a ton of help solve this problem.  I have a distribution (blue) that is made of two components.  I know a distribution of the first component (red) but not the second.  Is there any ways to predict or estimate the distribution of the second component ?  

Thanks in advance.

Re: Peak Prediction

I can use subtraction to guesstimate the distribution of the second but I don't know if subtraction gives me the accurate estimate of the second component.  I am assuming that a second distribution is near normal although I have no concrete evidence for that, and  a proportion of the first distribution shown in a previous graph is misleading.  It is actually an overly graph of the suspected first component (red) and the distribution in question with proportions being normalized (y-axis). 

Anyway, what I was really hoping was that JMP had some  functions that help me to build a model for two  component normal mixture, by which I could pick the best overall distribution that would resemble the mixed distribution in question.  Maybe what I need is FMM or EM scripts ?

Re: Peak Prediction

Seems like you have only one parameter to estimate in this problem : the proportion represented by the first component in your distribution. Given a proportion, the shape ofthe second component can be found by subtraction. But then, what would like to optimize? Do you have a hypothesis about the shape of the second component? Is it supposed to be the same as the first component? Is it supposed to be normally distributed?

PG

Re: Peak Prediction

PG,

Thanks for a suggestion.  I tried FMM but it was not sensitive enough to predict two distinctive distributions even though I manually  played with  some parameters.

Aki

Re: Peak Prediction

The first component looks left censored. Check procedure FMM for finite mixture models estimation.

PG