Description Usage Arguments Value
The function simulates a MC3/RMC3 chain of length nsamples using the scale, base and burn in taken optimally as default or specified by user. beta_set is the set of inverse temperatures chosen using select_inverse_temp() function, either under fixed scheme (MC3) or under randomized scheme (RMC3)
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target_pdf |
The log target density function from which the user wants to generate samples. |
beta_set |
The vector of inverse temperatures used (see select_inverse_temp() function to choose this vector appropriately). |
scale |
The proposal density scaling parameter. An approximation of the optimal scaling given the target_pdf is performed by OptimalScaling(). The default scale is this estimated optimal scaling |
base |
The starting value of the chain |
nsamples |
The number of samples to be drawn. |
cycle |
The number of iterations of RWMH chaining that is followed by a swap, or gap between consecutive swaps.Default is nsamples *0.01, rounded to next integer |
verb |
logical parameter, if TRUE the function prints the progress of simulation. |
swap_adjacent |
logical parameter, whether we allow for swaps between only consecutive inverse temperatures or any randomly chosen inverse temperatures pair. Default is TRUE. |
burn_in |
The number of samples assigned as burn-in period. The default burn-in is taken to be one-third of nsamples. |
Returns a list containing the following items
chain_set |
A list of chains at different underlying inverse temperatures produced by the MC3/RMC3 algorithm. |
post.mean |
The estimated posterior mean for the principal chain (inverse temp=1) adjusting for burn-in. |
@author Kushal K Dey
@useDynLib tmcmcR @export
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