Dobson's book does talk about modeling with distributions of various exponential families, and the modeling software we used did test different things using a variety of distributions, not just normal.
The small niggle is that you can test whether the residuals are normally distributed, then test if they are Fischer, and end up with p values 0.1 and 0.01. Fischer looks better, but normal is also ok. (In this contrived result)
Also, to my mind, autocorrelations affect the number of degrees of freedom. But if the test holds for a large range of degrees of freedom, it may not matter.
no subject
Dobson's book does talk about modeling with distributions of various exponential families, and the modeling software we used did test different things using a variety of distributions, not just normal.
The small niggle is that you can test whether the residuals are normally distributed, then test if they are Fischer, and end up with p values 0.1 and 0.01. Fischer looks better, but normal is also ok. (In this contrived result)
Also, to my mind, autocorrelations affect the number of degrees of freedom. But if the test holds for a large range of degrees of freedom, it may not matter.