Description Usage Arguments Value Author(s) References Examples
This function runs a Metropolis-Hastings algorithm on a posterior distribution associated with a
mixture model and 500 datapoints. Depending on the value of the boolean indicator lange
, the function
uses a regular Gaussian random-walk proposal or a Langevin alternative.
1 |
Niter |
Number of MCMC iterations |
lange |
Boolean variable indicating the use of the Langevin alternative |
scale |
Scale factor of the Gaussian perturbation |
The function returns a plot of the log-posterior surface, along with the MCMC sample represented both by points and lines linking one value to the next.
Christian P. Robert and George Casella
Chapter 6 of EnteR Monte Carlo Statistical Methods
1 2 | ## Not run: mhmix(Nit=10^3,scale=2)
#you can also try mhmix(lange=TRUE,scale=.1)
|
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