Table 4 Posterior summaries of simulation due to stationary samples using the function LaplacesDemon
From: Bayesian analysis of generalized log-Burr family with R
Logistic model (k =1) | |||||||
|---|---|---|---|---|---|---|---|
Parameter | Mean | SD | MCSE | ESS | LB | Median | UB |
Beta | 5.10 | 0.10 | 0.01 | 481.56 | 4.92 | 5.10 | 5.30 |
Log.sigma | -0.92 | 0.16 | 0.01 | 427.68 | -1.25 | -0.91 | -0.59 |
Deviance | 149.55 | 2.31 | 0.18 | 360.81 | 147.27 | 149.05 | 155.11 |
LP | -86.27 | 1.15 | 0.09 | 360.82 | -89.05 | -86.02 | -85.13 |
Sigma | 0.40 | 0.07 | 0.00 | 442.40 | 0.29 | 0.40 | 0.55 |
Weibull model (k =30) | |||||||
Parameter | Mean | SD | MCSE | ESS | LB | Median | UB |
Beta | 5.24 | 0.10 | 0.01 | 373.50 | 5.07 | 5.22 | 5.46 |
Log.sigma | -0.80 | 0.16 | 0.01 | 360.03 | -1.11 | -0.79 | -0.50 |
Deviance | 149.62 | 2.14 | 0.15 | 334.67 | 147.55 | 148.94 | 155.09 |
LP | -86.31 | 1.07 | 0.07 | 334.66 | -89.04 | -85.97 | -85.27 |
Sigma | 0.46 | 0.07 | 0.00 | 373.10 | 0.33 | 0.45 | 0.61 |