Inference for Bugs model at "/home/kubo/Andrew_strep/model.bug.txt", fit using WinBUGS, 3 chains, each with 3000 iterations (first 1000 discarded), n.thin = 10 n.sims = 600 iterations saved mean sd 2.5% 25% 50% 75% 97.5% Rhat n.eff beta[1] 5.750 1.140 3.388 5.028 5.775 6.543 7.758 1.006 520 beta[2] 0.823 0.098 0.643 0.762 0.817 0.889 1.014 1.002 600 beta[3] 1.535 0.911 -0.110 0.877 1.473 2.222 3.222 1.014 150 beta[4] -6.695 1.651 -10.050 -7.826 -6.630 -5.590 -3.599 1.011 230 beta[5] -4.125 1.357 -6.757 -4.999 -4.143 -3.239 -1.434 1.014 130 beta[6] -1.573 1.408 -4.135 -2.511 -1.588 -0.653 1.285 1.022 95 beta[7] 1.177 1.619 -1.962 0.245 1.191 2.240 4.424 1.038 57 r[1] -2.467 1.565 -5.624 -3.538 -2.425 -1.443 0.489 1.006 270 r[2] 4.883 1.172 2.756 4.124 4.770 5.700 7.246 1.036 73 r[3] 1.947 1.173 -0.357 1.172 1.952 2.765 4.125 1.027 77 r[4] -0.264 1.481 -3.191 -1.194 -0.307 0.649 2.565 1.017 160 r[5] -2.361 1.229 -4.800 -3.164 -2.359 -1.482 0.141 1.014 130 r[6] -4.175 1.154 -6.468 -4.955 -4.126 -3.459 -2.100 1.044 49 r[7] 1.911 1.763 -1.356 0.736 1.885 3.093 5.563 1.011 170 r[8] -4.136 1.325 -6.701 -4.992 -4.187 -3.208 -1.584 1.021 110 r[9] 2.347 1.555 -0.861 1.359 2.355 3.327 5.442 1.000 600 r[10] -1.843 1.426 -4.533 -2.828 -1.841 -0.851 0.877 1.002 590 r[11] 0.347 1.358 -2.276 -0.590 0.391 1.260 2.906 1.009 220 r[12] 2.015 1.337 -0.670 1.134 1.984 2.855 4.722 1.008 250 r[13] -0.014 1.456 -2.688 -1.051 -0.038 0.925 2.949 1.004 600 r[14] 1.153 1.261 -1.365 0.338 1.250 1.953 3.561 1.024 96 r[15] -0.001 1.830 -3.519 -1.308 0.011 1.199 3.676 1.006 250 r[16] -4.025 1.437 -6.595 -5.055 -3.953 -3.053 -1.478 1.008 250 r[17] -0.835 1.349 -3.640 -1.687 -0.866 -0.002 1.735 1.013 140 r[18] 1.054 1.307 -1.506 0.214 1.053 1.944 3.729 1.003 600 r[19] -0.281 1.238 -2.743 -1.107 -0.322 0.570 2.244 1.006 280 r[20] 0.216 1.453 -2.599 -0.714 0.223 1.087 3.078 1.015 140 r[21] 4.476 1.621 1.350 3.433 4.479 5.663 7.401 1.004 410 r[22] 4.171 1.699 0.878 3.014 4.207 5.228 7.638 1.000 600 r[23] -3.201 2.254 -7.943 -4.525 -3.133 -1.647 0.780 0.999 600 r[24] -2.317 2.412 -7.355 -3.891 -2.133 -0.719 2.027 1.005 350 r[25] -4.150 2.073 -8.882 -5.389 -3.919 -2.720 -0.585 1.010 230 r[26] 0.077 1.710 -3.108 -1.071 0.004 1.217 3.579 1.011 230 r[27] 0.338 1.645 -2.589 -0.799 0.367 1.390 3.540 1.004 600 r[28] 2.511 1.343 -0.155 1.590 2.514 3.338 5.118 1.014 150 r[29] 3.911 1.152 1.680 3.115 3.890 4.746 6.082 1.024 120 r[30] 1.347 1.177 -0.868 0.583 1.326 2.076 3.757 1.009 190 r[31] 0.515 1.310 -2.137 -0.306 0.584 1.364 2.958 1.055 40 r[32] -6.762 1.759 -10.381 -7.935 -6.636 -5.479 -3.773 1.004 390 r[33] 1.115 1.284 -1.446 0.249 1.210 1.991 3.430 1.047 47 r[34] 0.070 1.196 -2.330 -0.731 0.096 0.920 2.379 1.015 120 r[35] 3.881 1.158 1.526 3.108 3.876 4.660 6.145 1.031 110 r[36] -0.270 1.270 -2.753 -1.101 -0.267 0.580 2.168 1.043 50 r[37] 1.501 1.167 -0.815 0.658 1.566 2.275 3.744 1.031 71 r[38] -1.054 1.419 -3.871 -1.850 -1.012 -0.209 1.645 1.018 110 r[39] 0.386 1.160 -1.830 -0.368 0.450 1.126 2.613 1.059 38 r[40] 1.295 1.256 -1.266 0.508 1.308 2.176 3.848 1.046 47 r[41] -1.476 1.163 -3.710 -2.243 -1.470 -0.695 0.712 1.029 75 r[42] -2.093 1.167 -4.477 -2.881 -2.106 -1.263 0.138 1.029 75 r[43] 3.199 1.158 0.879 2.442 3.171 3.932 5.418 1.119 78 r[44] -8.667 1.746 -12.191 -9.708 -8.561 -7.480 -5.474 1.007 430 r[45] 0.302 1.215 -1.932 -0.466 0.236 1.117 2.777 1.010 170 r[46] 0.702 1.766 -2.723 -0.522 0.631 1.986 4.173 1.027 73 r[47] 3.269 1.140 1.063 2.464 3.286 4.050 5.604 1.033 66 r[48] 1.158 1.133 -1.099 0.455 1.191 1.906 3.317 1.048 45 r[49] 0.580 1.286 -1.950 -0.294 0.612 1.389 3.073 1.040 52 r[50] 1.104 1.144 -1.154 0.325 1.188 1.865 3.216 1.062 36 tau.individual 0.107 0.028 0.059 0.086 0.104 0.125 0.169 1.007 300 tau.noise 0.256 0.024 0.211 0.240 0.254 0.271 0.306 1.000 600 deviance 3213.373 27.158 3163.975 3195.000 3213.000 3231.000 3271.025 1.003 420 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 = Dbar-Dhat) pD = 364.6 and DIC = 3578.0 DIC is an estimate of expected predictive error (lower deviance is better).