I'd like to test how well my data can be modeled by an Exponentially modified Gaussian distribution (Wikipedia) or Normal-exponential-gamma (NEG) Distribution. However, the parameter estimation (which involves Skewness) is not very robust when there are outliers in the data set.
I've good experiences with Median based parameter estimation on this data set (see the related question Estimating parameters of a normal distribution: median instead of mean? ).
Do you know a Median-based or similarly robust parameter estimation for the ExGaussian / NEG distributions? I've already tried trimming my data set, the results were clearly better afterwards. Yet, this obviously introduces a bias, that I would need to correct somehow.