Description Usage Arguments Value Author(s) See Also Examples

**Experimental** Metropolis-Hastings algorithm, which tries
to adjust a transition matrix such that its stationary distribution
becomes approximately equal to a prespecified probability vector.

1 | ```
adaptP(P, target, niter = 1e+06)
``` |

`P` |
a transition matrix, i.e., a square matrix where all rows sum to 1. |

`target` |
the stationary probability vector to approximate. |

`niter` |
the number of iterations of the MCMC algorithm |

the adjusted transition matrix.

Leonhard Held

`C2pop`

for an alternative method.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## a row-normalized contact matrix
C <- matrix(c(0.8, 0.1, 0.1,
0.2, 0.6, 0.2,
0.1, 0.2, 0.7), byrow=TRUE, ncol=3, nrow=3)
stationary(C)
## population fractions define the target distribution
popfracs <- c(0.4, 0.3, 0.3)
## adapt 'C' to the given population fractions
Cpop <- adaptP(C, popfracs, niter = 50000)
stationary(Cpop)
## this method increases the diagonal values of 'C'
round(C, 3)
round(Cpop, 3)
round(Cpop/C, 3)
``` |

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