In my self-study, I have read the wikipedia entries and some books in regards to M-estimators and L-estimators.
I understand that M-estimators are so called "M" because they "Maximize" the likelihood function, and/or functions of the data itself. I also understand that L-estimators are so called because they use "Linear" combinations of order-statistics of the data.
It seems to me though that there are overlaps between M-estimators and L-estimators, is this not correct? (For example, the mean seems to me that it can be derived as an M-estimator, or as an L-estimator).
Put another way, if we were to draw a Venn Diagram of all M and L estimators, how much would they overlap with each other, if at all?
Edit:
Thanks to the feedback, I understand that such a Venn Diagram might have infinite elements. What I would like however, is very rough percentages of overlap, based on ones' experience, since I know that this experience is far greater than mine! I am just after a rough estimate based on what experts and practitioners in the field have seen and come across.
Thank you.