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.
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.
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?
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 ?