sample_tmb_rwm {adnuts} | R Documentation |
[Deprecated] Draw MCMC samples from a model posterior using a Random Walk Metropolis (RWM) sampler.
sample_tmb_rwm(
iter,
fn,
init,
alpha = 1,
chain = 1,
warmup = floor(iter/2),
thin = 1,
seed = NULL,
control = NULL
)
iter |
The number of samples to draw. |
fn |
A function that returns the log of the posterior density. |
init |
A list of lists containing the initial parameter
vectors, one for each chain or a function. It is strongly
recommended to initialize multiple chains from dispersed
points. A of NULL signifies to use the starting values
present in the model (i.e., |
alpha |
The amount to scale the proposal, i.e,
Xnew=Xcur+alpha*Xproposed where Xproposed is generated from a mean-zero
multivariate normal. Varying |
chain |
The chain number, for printing only. |
warmup |
The number of warmup iterations. |
thin |
The thinning rate to apply to samples. Typically not used with NUTS. |
seed |
The random seed to use. |
control |
A list to control the sampler. See details for further use. |
This algorithm does not yet contain adaptation of alpha
so some trial and error may be required for efficient sampling.
A list containing samples and other metadata.
Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., Teller, E., 1953. Equation of state calculations by fast computing machines. J Chem Phys. 21:1087-1092.