Description Usage Arguments Details Value References See Also
Generate a sample from a probability distribution with the shrinking-rank slice sampling method.
1 2 | shrinking.rank.sample(target.dist, x0, sample.size, tuning=1,
downscale=0.95, min.dimension=1)
|
target.dist |
Target distribution; see |
x0 |
Numeric vector containing initial state. |
sample.size |
Requested sample size. |
tuning |
A tuning parameter; corresponds to σ_c in sec. 5 of Thompson and Neal (2010). |
downscale |
Factor to reduce crumb standard deviation by when a proposal is rejected. |
min.dimension |
The minimum dimension to sample crumbs from. |
shrinking.rank.slice.sample
implements the shrinking-rank
method of slice sampling, as described by Thompson and Neal (2010). It
can be passed to compare.samplers
in the samplers
list argument.
A list with elements X
, evals
, and grads
,
following the calling convention of compare.samplers
.
Thompson, M. B. and Neal, R. M. (2010). Covariance-adaptive slice sampling. Technical Report TR-1002, Dept. of Statistics, University of Toronto.
compare.samplers
cov.match.sample
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