Adaptive MetropolisHastings algorithm, with parallel chains. The adaptation is such that it targets an acceptance rate.
1  adaptiveMH(target, AP, proposal, verbose)

target 
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 (componentwise) of each chain. 
Luke Bornn <bornn@stat.harvard.edu>, Pierre E. Jacob <pierre.jacob.work@gmail.com>
preexplorationAMH
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