Description Usage Arguments Value Examples

Calculate each chain separately for the mean (across many MCMC iterations)
of posterior log-likelihood. If the difference of the means and
the median (across chains) of the mean of posterior is greater than the
`cut`

, chains are considered stuck. The default value for `cut`

is 10. `unstick`

manually removes stuck chains from posterior samples.

1 2 |

`x` |
posterior samples |

`hyper` |
whether x are hierarhcial samples |

`cut` |
a criterion deciding if a chain is stuck. |

`start` |
start to evaluate from which iteration. |

`end` |
end at which iteration for evaeuation. |

`verbose` |
a boolean switch to print more information |

`digits` |
print how many digits. Default is 2 |

`PickStuck`

gives an index vector; `unstick`

gives a DMC
sample.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
model <- BuildModel(
p.map = list(A = "1", B = "1", t0 = "1", mean_v = "M", sd_v = "1", st0 = "1"),
match.map = list(M = list(s1 = 1, s2 = 2)),
factors = list(S = c("s1", "s2")),
constants = c(st0 = 0, sd_v = 1),
responses = c("r1", "r2"),
type = "norm")
p.vector <- c(A = .75, B = .25, t0 = .2, mean_v.true = 2.5, mean_v.false = 1.5)
p.prior <- BuildPrior(
dists = c("tnorm", "tnorm", "beta", "tnorm", "tnorm"),
p1 = c(A = .3, B = .3, t0 = 1, mean_v.true = 1, mean_v.false = 0),
p2 = c(1, 1, 1, 3, 3),
lower = c(0, 0, 0, NA, NA),
upper = c(NA,NA, 1, NA, NA))
## Not run:
dat <- simulate(model, 30, ps = p.vector)
dmi <- BuildDMI(dat, model)
sam <- run(StartNewsamples(5e2, dmi, p.prior))
bad <- PickStuck(sam)
## End(Not run)
``` |

ggdmc documentation built on Sept. 2, 2018, 1:03 a.m.

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