Description Usage Arguments Value
The function simulates adaptive TMCMC chain of length nsamples using one of the three methods of adaptation - SCAM, Atchade and RAMA (analogously defined as in RWMH case).
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target_pdf |
The target density function from which the user wants to generate samples. |
base |
The starting value of the chain |
nsamples |
The number of samples to be drawn using the TMCMC algorithm. |
def.scale |
the initial scale of the proposal chosen, on which we update adaptively. Default is 1. |
burn_in |
The number of samples assigned as burn-in period. The default burn-in is taken to be one-third of nsamples. |
a_rama |
The scaling used in RAMA if norm of the chain at current iterate is less than dimension. |
b_rama |
The scaling used in RAMA if norm of the chain at current iterate is greater than dimension. |
M_rama |
The bounds on a_rama and b_rama, lower bound is -M_rama, upper bound is M_rama. |
atchade_low |
The lower bound of scale for Atchade scheme |
atchade_high |
The upper bound of scale for Atchade scheme |
method |
The method of adaptation used for generating the chain. May be one of 3 types- SCAM, Atchade and the RAMA methods. |
verb |
logical parameter, if TRUE the function prints the progress of simulation. |
Returns a list containing the following items
chain |
The full chain produced by the adaptive TMCMC method with user-chosen method of adaptation. |
post.mean |
The estimated posterior mean of the adaptive TMCMC chain adjusting for burn-in. |
@author Kushal K Dey
@useDynLib tmcmcR @export
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