Table 2
Summaries of the Bayesian estimation.
| copula | prior | mean | s-m | sd | 2.5% | 25% | 50% | 75% | 97.5% | n_eff | Rhat |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Frank | NI | −23.936 | 0.062 | 2.185 | −28.396 | −25.384 | −23.854 | −22.440 | −19.903 | 1255 | 1.006 |
| Frank | I | −24.108 | 0.061 | 2.139 | −28.376 | −25.593 | −24.057 | −22.614 | −20.035 | 1216 | 1.001 |
| Gaussian | NI | −0.953 | 0.000 | 0.007 | −0.965 | −0.957 | −0.953 | −0.948 | −0.937 | 1458 | 1.000 |
| Gaussian | I | −0.953 | 0.000 | 0.007 | −0.965 | −0.958 | −0.954 | −0.949 | −0.937 | 1210 | 1.002 |
n_eff: final number of simulations used for the estimation; sd: standard deviation; s–m=sd/n_eff1/2; Rhat: potential scale reduction factor on split chains (at convergence, Rhat = 1). In bold letter the Bayesian estimates of θ for Frank and ρ for Gaussian copula, by quadratic loss function on left, by multi linear loss function on right. Non-Informative (NI) prior on top and Informative (I) prior on bottom.
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