Inference for Bugs model at "/home/kubo/masaki_shoot/winbugs/model.bug.txt", fit using WinBUGS, 3 chains, each with 2000 iterations (first 1000 discarded), n.thin = 5 n.sims = 600 iterations saved mean sd 2.5% 25% 50% 75% 97.5% Rhat n.eff bb[1] -0.870 0.185 -1.205 -0.997 -0.869 -0.745 -0.500 1.030 73 bb[2] -0.118 0.063 -0.240 -0.158 -0.117 -0.079 0.006 1.003 600 bs[1,1] -0.608 0.233 -1.072 -0.766 -0.610 -0.440 -0.169 1.027 83 bs[1,2] -0.831 0.268 -1.357 -1.003 -0.840 -0.658 -0.330 1.014 130 bs[1,3] -0.207 0.228 -0.625 -0.344 -0.218 -0.073 0.246 1.031 70 bs[1,4] -0.166 0.337 -0.852 -0.372 -0.171 0.052 0.439 1.000 600 bs[1,5] 1.001 0.233 0.536 0.831 0.988 1.170 1.474 1.021 94 bs[1,6] 0.459 0.237 0.004 0.296 0.456 0.614 0.906 1.005 340 bs[1,7] 0.449 0.323 -0.125 0.232 0.434 0.660 1.100 1.019 130 bs[1,8] 0.711 0.236 0.230 0.546 0.703 0.880 1.174 1.012 240 bs[1,9] 0.465 0.227 0.033 0.317 0.473 0.624 0.882 1.037 62 bs[1,10] -0.298 0.265 -0.811 -0.479 -0.295 -0.112 0.203 1.016 140 bs[1,11] 0.241 0.237 -0.219 0.070 0.233 0.410 0.701 1.009 190 bs[1,12] -0.793 0.234 -1.253 -0.955 -0.786 -0.637 -0.355 1.013 150 bs[1,13] -0.199 0.230 -0.661 -0.354 -0.197 -0.036 0.235 1.017 120 bs[2,1] 0.178 0.093 0.029 0.110 0.175 0.236 0.377 1.001 600 bs[2,2] -0.029 0.151 -0.365 -0.118 -0.024 0.061 0.287 1.008 220 bs[2,3] 0.018 0.103 -0.174 -0.049 0.015 0.082 0.232 1.001 600 bs[2,4] -0.075 0.120 -0.312 -0.160 -0.068 0.010 0.143 1.008 210 bs[2,5] -0.009 0.107 -0.214 -0.080 -0.010 0.058 0.193 1.004 470 bs[2,6] -0.018 0.130 -0.270 -0.102 -0.017 0.058 0.248 0.999 600 bs[2,7] -0.032 0.147 -0.330 -0.124 -0.027 0.061 0.240 1.003 470 bs[2,8] -0.084 0.084 -0.250 -0.136 -0.084 -0.027 0.073 1.001 600 bs[2,9] 0.024 0.104 -0.177 -0.041 0.021 0.086 0.253 1.005 470 bs[2,10] -0.029 0.113 -0.269 -0.103 -0.025 0.044 0.189 1.000 600 bs[2,11] -0.131 0.091 -0.302 -0.193 -0.130 -0.071 0.038 1.003 520 bs[2,12] 0.150 0.106 -0.043 0.075 0.143 0.223 0.379 1.004 400 bs[2,13] 0.030 0.130 -0.253 -0.047 0.033 0.110 0.290 1.000 600 tau.tree 9.777 2.023 6.167 8.173 9.705 11.142 13.840 1.002 600 tau.bs[1] 2.788 1.269 0.945 1.893 2.543 3.536 5.614 1.002 600 tau.bs[2] 61.236 44.597 12.416 31.930 49.400 78.382 169.322 1.001 600 deviance -237.013 16.442 -267.220 -247.725 -238.150 -225.150 -204.190 1.000 600 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 = 132.7 and DIC = -104.4 DIC is an estimate of expected predictive error (lower deviance is better).