Are there any existing R packages capable of performing a robust linear regression on complex valued data?
I have a set $Y$ of complex valued ($a + b i$) data, that are linearly dependent on another set $X$. I need to find the (complexed valued) slope and intercept of the relationship $Y = m X + b$ that best fits the data.
I've implemented an ordinary least-squares fitting in R, per Whuber's excellent answer. However, there are a significant number of outliers among my data, so this method often fails to give useful results. So I'm looking to use a robust fit instead.
Unfortunately, I haven't been able to find much information on applying such fits to complex data. This paper has the best overview I've seen so far. I have found the rlm function in the MASS library, but it's only set up to handle real numbers. I could modify the source of it to handle them, but I don't really understand it.
Does anyone know of a library that has a robust linear fit function that can handle complex numbers?