Suppose we had an expressions that was proportional to
$$\frac{1}{\sigma^{3}}\exp(\frac{-\beta}{\sigma^{2}})$$
My question is, can you choose different possible parametrization for a prior distribution?
you could choose a prior, $$\frac{1}{\sigma^{2}} \sim Gamma(1/2,\beta)$$
Or you could choose
$$\sigma^{2} \sim Inverse-Gamma(\frac{5}{2},\beta)$$
which correspond to different kernels..
It seems we could take either, but the kernel would then be different leading to differences in integration and such.
So what is it I am missing here? Could you really just choose either one even though they lead to different inferences( I suppose because $1/x^{2}$ is not invariant?