Inference for Bugs model at "two_component_exclude_high_stress_unconfined.jags", fit using jags,
 3 chains, each with 4e+06 iterations (first 10000 discarded), n.thin = 20
 n.sims = 598500 iterations saved
          mu.vect sd.vect   2.5%    25%    50%    75%  97.5%  Rhat  n.eff
A_GBS_log   2.187   0.538  1.085  1.835  2.205  2.555  3.194 1.001  23000
A_dis_log   6.560   1.057  4.341  5.903  6.603  7.279  8.497 1.001   4500
Q_GBS      63.385   2.606 58.234 61.645 63.403 65.143 68.468 1.001   5300
Q_dis      70.143   4.989 59.890 66.964 70.276 73.522 79.498 1.001   4800
n_GBS       2.283   0.108  2.064  2.212  2.285  2.357  2.488 1.001 140000
n_dis       3.770   0.158  3.521  3.659  3.748  3.857  4.142 1.001  42000
p           1.107   0.074  0.967  1.056  1.105  1.155  1.256 1.001   4800
deviance   30.787   6.227 19.294 26.506 30.533 34.785 43.755 1.001 190000

For each parameter, n.eff is a crude measure of effective sample size,
and Rhat is the potential scale reduction factor (at convergence, Rhat=1).

DIC info (using the rule, pD = var(deviance)/2)
pD = 19.4 and DIC = 50.2
DIC is an estimate of expected predictive error (lower deviance is better).

Iterations = 10001:3999981
Thinning interval = 20 
Number of chains = 3 
Sample size per chain = 199500 

1. Empirical mean and standard deviation for each variable,
   plus standard error of the mean:

            Mean      SD  Naive SE Time-series SE
A_dis_log  6.560 1.05689 0.0013662      0.0162079
A_GBS_log  2.187 0.53842 0.0006960      0.0055754
deviance  30.787 6.22686 0.0080489      0.0216893
n_dis      3.770 0.15816 0.0002044      0.0006843
n_GBS      2.283 0.10804 0.0001397      0.0006019
p          1.107 0.07403 0.0000957      0.0003817
Q_dis     70.143 4.98879 0.0064486      0.0750817
Q_GBS     63.385 2.60609 0.0033687      0.0257279

2. Quantiles for each variable:

             2.5%    25%    50%    75%  97.5%
A_dis_log  4.3409  5.903  6.603  7.279  8.497
A_GBS_log  1.0847  1.835  2.205  2.555  3.194
deviance  19.2940 26.506 30.533 34.785 43.755
n_dis      3.5210  3.659  3.748  3.857  4.142
n_GBS      2.0643  2.212  2.285  2.357  2.488
p          0.9669  1.056  1.105  1.155  1.256
Q_dis     59.8899 66.964 70.276 73.522 79.498
Q_GBS     58.2338 61.645 63.403 65.143 68.468

Potential scale reduction factors:

          Point est. Upper C.I.
A_dis_log          1          1
A_GBS_log          1          1
deviance           1          1
n_dis              1          1
n_GBS              1          1
p                  1          1
Q_dis              1          1
Q_GBS              1          1

Multivariate psrf

1
