Inference for Bugs model at "../Mi model JAGS simp7.txt", fit using jags,
 3 chains, each with 4e+05 iterations (first 2e+05 discarded), n.thin = 300
 n.sims = 1998 iterations saved
         mu.vect sd.vect    2.5%    25%    50%    75%  97.5%  Rhat n.eff
Loc[1]     1.748   0.062   1.629  1.705  1.748  1.790  1.869 1.001  1700
Loc[2]     1.980   0.069   1.850  1.933  1.982  2.025  2.118 1.001  1600
alpha[1]   2.120  19.812 -40.411  0.476  1.867  3.465 47.149 1.005   620
alpha[2]  -0.136   0.071  -0.282 -0.183 -0.136 -0.088 -0.001 1.000  2000
alpha[3]   0.135   0.074  -0.007  0.085  0.133  0.183  0.283 1.001  2000
alpha[4]   0.214   0.043   0.131  0.187  0.214  0.242  0.298 1.000  2000
alpha[5]  -0.312   0.065  -0.444 -0.353 -0.309 -0.268 -0.187 1.001  2000
alpha[6]   0.282   0.101   0.061  0.222  0.290  0.351  0.459 1.000  2000
alpha[7]  -0.148   0.109  -0.362 -0.219 -0.150 -0.078  0.075 1.000  2000
delta     -2.046   0.584  -3.147 -2.471 -2.065 -1.659 -0.816 1.001  2000
p.val[1]   0.459   0.842   0.000  0.000  0.000  0.000  2.000 1.002  1200
p.val[2]   1.950   0.312   1.850  2.000  2.000  2.000  2.000 1.010  1900
p.val[3]   0.068   0.363   0.000  0.000  0.000  0.000  2.000 1.008  1700
p.val[4]   0.000   0.000   0.000  0.000  0.000  0.000  0.000 1.000     1
p.val[5]   2.000   0.000   2.000  2.000  2.000  2.000  2.000 1.000     1
p.val[6]   0.018   0.189   0.000  0.000  0.000  0.000  0.000 1.000  2000
p.val[7]   1.831   0.557   0.000  2.000  2.000  2.000  2.000 1.002  2000
tau       14.909   2.784   9.867 12.930 14.820 16.655 21.004 1.002  1100
deviance  10.435   5.505   1.897  6.441  9.761 13.534 23.498 1.003   880

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 = 15.1 and DIC = 25.6
DIC is an estimate of expected predictive error (lower deviance is better).