So I know if the variance of Y is nonconstant you can do a weighted linear regression.
And if the variance of X is nonzero then there is Total Least Squares regression.
But how would you take into account errors in both Y and X that are nonconstant (and nonzero)?
Like is there a way people have extended weighted regression to Total Least Squaeres? How about extension of GLMs to include errors in X?