Hey,
I got a problem here:
I measured a distribution, let us call it Z. Now, I know that this distribution Z is a convolution of two different distribution. One of them is Gaussian distribution (G) with a known standard deviation. The other one is a distribution (D) , where the function is known, but we have some free parameters.
So, now I want to find the parameters for the distribution D, which outputs distribution Z best.
Anyone an idea?
Best regards from Germany,
Michael
The answer depends on many things.
What kind of distribution is D? It may or may not be reasonable to compute a symbolic representation of Z, which might affect how I’d go about solving this.
There are many ways to estimate the parameters of a distribution. These estimators have different properties for different situations. Do you know what these might be for your situation?
I guess the generic answer to the question is to use Convolve or a numerical equivalent to make a representation of Z. From there you can use EstimatedDistribution or any related functionality to estimate the parameters.