Output: Regression example

Posterior means, posterior standard deviations and 95% credible intervals (Inference->Samples->stats)

Sample path (history)

Posterior probability densities (Inference->Samples->density)

Sample autocorrelation function (Inference->Samples->auto corr)

Running quantile plot (Inference->Samples->quantiles)

Scatter plots (Inference->Correlations…)

Posterior predictive analysis. pleft:Pr(ypred[i] =< y[i]). pright: Pr(y.pred[i]>=y[i])

Inference-> Compare-> node:pleft and click on caterpillar)

(Further, right-click on the figure, Property…-> Margins -> Special…-> check “rank” and showbaseline:0.05)

*P(ystar[26]<y[26])=0.005 < 0.05

Inference-> Compare-> node:pright and click on caterpillar)

(Further, right-click on the figure, Property…-> Margins -> Special…-> check “rank” and showbaseline:0.05)

*P(ystar[28]>y[28])=0.0002 < 0.05

*P(ystar[29]>y[29])=0.0190 < 0.05

*P(ystar[18]>y[18])=0.0358 < 0.05