tfprobability: mcmc_uncalibrated_random_walk – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

mcmc_uncalibrated_random_walk

Generate proposal for the Random Walk Metropolis algorithm.

Description

Warning: this kernel will not result in a chain which converges to the target_log_prob. To get a convergent MCMC, use mcmc_random_walk_metropolis(...) or mcmc_metropolis_hastings(mcmc_uncalibrated_random_walk(...)).

Usage

mcmc_uncalibrated_random_walk(
  target_log_prob_fn,
  new_state_fn = NULL,
  seed = NULL,
  name = NULL
)

Arguments

`target_log_prob_fn`	Function which takes an argument like `current_state` ((if it's a list `current_state` will be unpacked) and returns its (possibly unnormalized) log-density under the target distribution.
`new_state_fn`	Function which takes a list of state parts and a seed; returns a same-type `list` of `Tensor`s, each being a perturbation of the input state parts. The perturbation distribution is assumed to be a symmetric distribution centered at the input state part. Default value: `NULL` which is mapped to `tfp$mcmc$random_walk_normal_fn()`.
`seed`	integer to seed the random number generator.
`name`	String name prefixed to Ops created by this function. Default value: `NULL` (i.e., 'rwm_kernel').

Value

a Monte Carlo sampling kernel

mcmc_uncalibrated_random_walk

Description

Usage

Arguments

Value

See Also

tfprobability

We don't support your browser anymore