-
Notifications
You must be signed in to change notification settings - Fork 1.1k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Provide a resimulation Metropolis TransitionKernel #218
Comments
Do you have a reference describing what this is? Does 'resimulation' mean the same thing as an independence sampler (i.e., always propose from the given distribution ignoring the current state of the chain)? |
Yes. At least, I meant constructing valid transition kernels from independence proposals. I don't know how standard or non-standard a term that is. |
One somewhat hacky way of implementing this is by creating a new kernel = tfp.mcmc.RandomWalkMetropolis(
target_log_prob_fn=...,
new_state_fn=resimulation_fn(tfd.Distribution)) EDIT: Nevermind, |
Symmetry is a useful assumption, because it lets you use proposals whose densities you can't evaluate -- as long as they are symmetric. I think it's reasonable for these two to be different classes. We could also add the class of asymmetric, dependent proposals with tractable densities. That looks like a TransitionKernel made out of a function that accepts the current state and emits a Distribution representing the (conditional) proposal. One would have invoke this function backwards to compute the corresponding term in the acceptance ratio. |
Idea for usage:
The text was updated successfully, but these errors were encountered: