BayesianTools (version 0.1.8)

M: The Metropolis Algorithm

Description

The Metropolis Algorithm (Metropolis et al. 1953)

Usage

M(
  startValue = NULL,
  iterations = 10000,
  nBI = 0,
  parmin = NULL,
  parmax = NULL,
  f = 1,
  FUN,
  consoleUpdates = 1000
)

Arguments

startValue

vector with the start values for the algorithm. Can be NULL if FUN is of class BayesianSetup. In this case startValues are sampled from the prior.

iterations

iterations to run

nBI

number of burnin

parmin

minimum values for the parameter vector or NULL if FUN is of class BayesianSetup

parmax

maximum values for the parameter vector or NULL if FUN is of class BayesianSetup

f

scaling factor

FUN

function to be sampled from or object of class bayesianSetup

consoleUpdates

interger, determines the frequency with which sampler progress is printed to the console

Author

Francesco Minunno

References

Metropolis, Nicholas, et al. "Equation of state calculations by fast computing machines." The journal of chemical physics 21.6 (1953): 1087-1092.