Description Usage Arguments Details Value Author(s) References Examples

This function produces a set of marginal likelihood estimates for moving block bootstrap observations. Its main use is for calculating the standard error associated to the thermodynamic integration and stepping-stone sampling estimates.

1 |

`x` |
A data frame with the folloging columns: |

`bl` |
Block lenghts. |

`nboot` |
Number of bootstrap observations to be analysed. |

`temp` |
It indicates the temperatures to be used in the analysis, for instance, c(1,3,K) considers the temperatures at those positions, where |

For a block length equal to 1 (`bl`

=1) the original bootstrap method for i.i.d. data is recovered. A block lenght greater than one allows to take into account a potential autocorrelation within the Markov chains. `mbb`

is being designed to take also into account potential cross-correlation between the Markov chains due to swaps in parallel tempering sampling. See more details in Maturana R. et al. (2018)

It produces a list with the following elements:

`Zs` |
Marginal likelihood estimates via |

`se` |
Standard deviation of the marginal likelihood estimates calculated for the bootstrap observations. |

`res` |
Marginal likelihood estimate differences between the ones calculated for the bootstrap observations and the original dataset |

Patricio Maturana Russel [email protected]

Kunsch, H. R. 1989. The Jackknife and the Bootstrap for General Stationary Observations. *The Annals of Statistics* **17**(3), 1217–1241.

Maturana Russel, P., Meyer, R., Veitch, J., and Christensen, N. 2018. The stepping-stone algorithm for calculating the evidence of gravitational wave models. arXiv preprint arXiv:1810.04488

1 2 3 | ```
data(ligoVirgoSim)
R = mbb(ligoVirgoSim, bl = 10, nboot = 20, temp = NULL)
R$se; # standard error of the marginal likelihood estimates
``` |

pmat747/powModSel documentation built on Dec. 7, 2018, 8 a.m.

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