nonadaptive.crumb.sample: Sample with nonadaptive-crumb slice sampling

In SamplerCompare: A Framework for Comparing the Performance of MCMC Samplers

Sample with nonadaptive-crumb slice sampling

Description

Generate a sample from a probability distribution with the nonadaptive-crumb slice sampling method.

Usage

nonadaptive.crumb.sample(target.dist, x0, sample.size,
                        tuning=1, downscale=0.95)

Arguments

target.dist	Target distribution; see make.dist.
x0	Numeric vector containing initial state.
sample.size	Requested sample size.
tuning	Initial crumb standard deviation.
downscale	Factor to reduce crumb standard deviation by when a proposal is rejected.

Details

This function implements slice sampling with nonadaptive crumbs. Crumbs are Gaussian with spherical covariance starting at tuning, decreasing by downscale each time a proposal is rejected. More information can be found in sec. 5.2 of Neal (2003). This function can be passed to compare.samplers in the samplers list argument.

Value

A list with elements X, evals, and grads, following the calling convention of compare.samplers.

References

Neal, Radford M. (2003), “Slice Sampling,” The Annals of Statistics 31(3):705-767.

See Also

shrinking.rank.sample, compare.samplers

SamplerCompare documentation built on April 24, 2023, 9:09 a.m.