Implements the Parallel Adaptive Wang-Landau algorithm.
1 |
target |
Object of class |
binning |
Object of class |
AP |
Object of class |
proposal |
Object of class |
verbose |
Object of class |
The function returns a list holding various information:
finalchains |
The last point of each chain. |
acceptrates |
The vector of acceptance rates at each step. |
sigma |
The vector of the standard deviations used by the MH kernel along the iterations. If the proposal was adaptive, this allows to check how the adaptation behaved. |
allchains |
If asked in the tuning parameters, the chain history. |
alllogtarget |
If asked in the tuning parameters, the associated log density evaluations. |
meanchains |
If asked in the tuning parameters, the mean (component-wise) of each chain. |
logthetahistory |
If asked in the tuning parameters, all the log theta penalties. |
and other quantities, that you can browse by calling "names(results)"
where "results"
is the output
of the function.
Luke Bornn <bornn@stat.harvard.edu>, Pierre E. Jacob <pierre.jacob.work@gmail.com>
adaptiveMH, binning
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
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