None of the nice assumptions underlying nice proofs of optimality apply.
Well, this is a matter of degree. There is a reason we use these tools in the first place. A good statistician must be quite aware of the underlying assumptions of each tool, if only so that they can switch to something else when warranted. (For instance, use “robust” methods which try to identify and appropriately discount outliers.)
A good statistician must be quite aware of the underlying assumptions of each tool
Well, of course.
and appropriately discount outliers
Heh. The word “appropriately” is a tricky one. There is a large variety of robust methods which use different ways of discounting outliers, naturally with different results. The statistician will need to figure out what’s “appropriate” in this particular case and proofs don’t help here.
Well, this is a matter of degree. There is a reason we use these tools in the first place. A good statistician must be quite aware of the underlying assumptions of each tool, if only so that they can switch to something else when warranted. (For instance, use “robust” methods which try to identify and appropriately discount outliers.)
Well, of course.
Heh. The word “appropriately” is a tricky one. There is a large variety of robust methods which use different ways of discounting outliers, naturally with different results. The statistician will need to figure out what’s “appropriate” in this particular case and proofs don’t help here.