Description Usage Arguments Details Value Author(s) References Examples

This function produces a thermodynamic integration estimate of the marginal likelihood given a set of log-likelihood values at different temperatures.

1 |

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

`actPlot` |
If it is |

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

Power posterior methods, among them thermodynamic integration, rely on a set of samples from different transitional distributions, connecting the prior and the posterior distributions, which is defined by the power posterior density

*p(θ) \propto L(x|θ)^{β} π(θ), *

where *θ* is the parameter vector, *0 ≤ β ≤ 1* is the inverse temperature, *x* is the data, *p(θ)* is the power posterior density, *L(x|θ)* is the likelihood function, and *π(θ)* is the prior density.

`ti`

uses the trapezoidal rule in the estimation (see more details in Lartillot and Philippe (2006)).

It produces a thermodynamic integration estimate.

Patricio Maturana Russel [email protected]

Lartillot, N., and Philippe, H. 2006. Computing Bayes factors using Thermodynamic Integration. *Systematic Biology* **55**(2), 195–207.

1 2 | ```
data(ligoVirgoSim)
ti(ligoVirgoSim, actPlot = TRUE, temp = NULL)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.