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When writing this package I implicitly assumed that that whenever the log density is finite, the gradient (and now the Hessian, see #101) are also.
So calling eg logdensity_and_gradient in the context of an MCMC sampler
logdensity_and_gradient
fx, Dfx = logdensity_and_gradient(f, x) if isfinite(fx) # proceed using DfX else # reject point end
The motivation for the non-finite log density is to provide an escape hatch for x being outside the support, non-convergent solvers, etc.
x
Should we
document that whenever the log density is finite, so are the gradient and the Hessian?
or allow cases of finite log density, with potentially non-finite gradient and Hessian? (What would be the use case?)
The text was updated successfully, but these errors were encountered:
Clarify finiteness assumptions, add function to check.
8edccac
Fixes #102.
Successfully merging a pull request may close this issue.
When writing this package I implicitly assumed that that whenever the log density is finite, the gradient (and now the Hessian, see #101) are also.
So calling eg
logdensity_and_gradient
in the context of an MCMC samplerThe motivation for the non-finite log density is to provide an escape hatch for
x
being outside the support, non-convergent solvers, etc.Should we
document that whenever the log density is finite, so are the gradient and the Hessian?
or allow cases of finite log density, with potentially non-finite gradient and Hessian? (What would be the use case?)
The text was updated successfully, but these errors were encountered: