Inference for Bugs model at "/home/kubo/tanabe/winbugs/model.bug.txt", fit using WinBUGS, 3 chains, each with 4000 iterations (first 2000 discarded), n.thin = 10 n.sims = 600 iterations saved mean sd 2.5% 25% 50% 75% 97.5% Rhat bb[1] 0.436 0.147 0.118 0.352 0.451 0.537 0.707 1.022 bb[2] 0.067 0.128 -0.198 -0.004 0.074 0.145 0.298 1.067 bb[3] 2.278 0.095 2.082 2.213 2.282 2.343 2.449 1.035 bb[4] 2.431 0.039 2.352 2.408 2.433 2.456 2.500 1.001 bb[5] 1.909 0.082 1.723 1.867 1.914 1.961 2.056 1.016 bb[6] 2.441 0.099 2.244 2.376 2.443 2.505 2.637 1.051 bc[1,1] -0.104 0.021 -0.145 -0.118 -0.105 -0.090 -0.062 1.004 bc[1,2] -0.030 0.030 -0.087 -0.050 -0.032 -0.010 0.032 1.030 bc[1,3] 0.203 0.186 -0.147 0.082 0.201 0.321 0.586 1.039 bc[1,4] -0.862 0.311 -1.533 -1.075 -0.839 -0.630 -0.342 1.011 bc[1,5] 0.309 0.153 0.018 0.209 0.306 0.406 0.639 1.044 bc[2,1] -0.087 0.022 -0.129 -0.102 -0.087 -0.072 -0.046 1.008 bc[2,2] -0.027 0.029 -0.085 -0.044 -0.027 -0.009 0.030 1.021 bc[2,3] 0.012 0.160 -0.299 -0.087 0.008 0.109 0.343 1.019 bc[2,4] -0.540 0.364 -1.321 -0.752 -0.503 -0.316 0.170 1.021 bc[2,5] 0.299 0.137 0.058 0.207 0.291 0.378 0.610 1.038 bc[3,1] 0.421 0.013 0.396 0.412 0.421 0.430 0.446 1.003 bc[3,2] 0.009 0.023 -0.038 -0.005 0.009 0.026 0.050 1.020 bc[3,3] 0.103 0.134 -0.152 0.009 0.097 0.197 0.367 1.052 bc[3,4] -0.096 0.278 -0.598 -0.302 -0.083 0.079 0.440 1.093 bc[3,5] 0.014 0.097 -0.182 -0.046 0.013 0.080 0.201 1.021 bc[4,1] 0.387 0.010 0.367 0.380 0.387 0.394 0.404 1.006 bc[4,2] 0.022 0.009 0.006 0.017 0.022 0.028 0.038 1.002 bc[4,3] -0.263 0.053 -0.368 -0.296 -0.263 -0.227 -0.161 1.000 bc[4,4] -0.124 0.099 -0.330 -0.182 -0.121 -0.062 0.057 1.046 bc[4,5] -0.055 0.035 -0.125 -0.075 -0.055 -0.031 0.009 1.001 bc[5,1] 0.236 0.018 0.198 0.224 0.237 0.248 0.271 1.000 bc[5,2] 0.063 0.017 0.032 0.050 0.063 0.074 0.096 1.000 bc[5,3] 0.328 0.102 0.156 0.255 0.323 0.392 0.547 1.002 bc[5,4] -0.288 0.202 -0.749 -0.407 -0.280 -0.155 0.096 1.028 bc[5,5] -0.076 0.076 -0.226 -0.127 -0.076 -0.024 0.076 1.004 bc[6,1] 0.411 0.015 0.383 0.400 0.410 0.421 0.439 1.001 bc[6,2] -0.083 0.025 -0.132 -0.100 -0.083 -0.068 -0.031 1.005 bc[6,3] -0.347 0.134 -0.588 -0.437 -0.348 -0.270 -0.055 1.049 bc[6,4] -0.010 0.307 -0.682 -0.192 0.007 0.173 0.600 1.028 bc[6,5] -0.168 0.104 -0.361 -0.240 -0.168 -0.100 0.050 1.012 bs[1,1] -0.106 0.200 -0.476 -0.245 -0.108 0.028 0.306 1.014 bs[1,2] 0.031 0.200 -0.366 -0.091 0.037 0.143 0.437 1.003 bs[1,3] -0.113 0.187 -0.446 -0.229 -0.125 -0.006 0.283 1.021 bs[1,4] 0.020 0.257 -0.570 -0.126 0.018 0.192 0.514 1.013 bs[1,5] 0.102 0.191 -0.277 -0.019 0.103 0.213 0.506 1.041 bs[1,6] -0.068 0.198 -0.430 -0.199 -0.079 0.047 0.321 1.014 bs[1,7] -0.008 0.187 -0.352 -0.130 -0.014 0.117 0.369 1.002 bs[1,8] -0.278 0.233 -0.750 -0.448 -0.273 -0.124 0.173 1.035 bs[1,9] 0.227 0.203 -0.187 0.098 0.232 0.369 0.603 1.084 bs[1,10] 0.140 0.255 -0.374 -0.032 0.141 0.320 0.623 1.089 bs[1,11] 0.192 0.257 -0.351 0.031 0.191 0.367 0.666 1.016 bs[1,12] -0.109 0.214 -0.536 -0.241 -0.114 0.042 0.284 1.038 bs[1,13] 0.088 0.206 -0.294 -0.045 0.083 0.224 0.485 1.029 bs[1,14] -0.300 0.168 -0.601 -0.413 -0.304 -0.190 0.038 1.013 bs[1,15] -0.173 0.227 -0.610 -0.314 -0.166 -0.024 0.250 1.003 bs[1,16] 0.295 0.222 -0.108 0.142 0.286 0.437 0.725 1.008 bs[1,17] -0.444 0.217 -0.862 -0.596 -0.440 -0.296 -0.013 1.018 bs[1,18] 0.039 0.180 -0.321 -0.079 0.043 0.162 0.373 1.008 bs[1,19] 0.207 0.205 -0.221 0.078 0.219 0.343 0.574 1.055 bs[1,20] 0.117 0.194 -0.256 -0.017 0.124 0.247 0.501 1.015 bs[1,21] 0.405 0.238 -0.051 0.240 0.409 0.563 0.858 1.019 bs[1,22] -0.107 0.191 -0.474 -0.236 -0.101 0.022 0.258 1.002 bs[1,23] -0.274 0.154 -0.582 -0.371 -0.285 -0.168 0.040 1.010 bs[1,24] 0.530 0.253 0.054 0.347 0.524 0.704 1.052 1.016 bs[1,25] 0.047 0.194 -0.347 -0.075 0.035 0.165 0.439 1.008 bs[1,26] -0.039 0.186 -0.395 -0.161 -0.042 0.092 0.303 1.000 bs[1,27] -0.392 0.298 -0.914 -0.625 -0.415 -0.169 0.192 1.058 bs[1,28] -0.074 0.205 -0.489 -0.197 -0.069 0.061 0.304 1.001 bs[1,29] 0.166 0.198 -0.199 0.021 0.155 0.305 0.553 1.017 bs[2,1] -0.027 0.195 -0.381 -0.154 -0.038 0.098 0.368 1.046 bs[2,2] -0.176 0.197 -0.548 -0.308 -0.189 -0.042 0.224 1.044 bs[2,3] -0.083 0.165 -0.410 -0.196 -0.088 0.022 0.260 1.058 bs[2,4] -0.068 0.243 -0.535 -0.223 -0.057 0.084 0.390 1.029 bs[2,5] -0.295 0.175 -0.606 -0.420 -0.307 -0.167 0.045 1.010 bs[2,6] -0.007 0.189 -0.362 -0.132 -0.011 0.121 0.355 1.029 bs[2,7] -0.244 0.180 -0.568 -0.369 -0.253 -0.120 0.126 1.038 bs[2,8] 0.204 0.174 -0.142 0.085 0.206 0.323 0.537 1.004 bs[2,9] -0.047 0.165 -0.395 -0.153 -0.029 0.064 0.249 1.005 bs[2,10] 0.225 0.191 -0.180 0.090 0.241 0.362 0.551 1.006 bs[2,11] 0.148 0.245 -0.371 0.014 0.157 0.299 0.594 1.048 bs[2,12] 0.228 0.197 -0.179 0.104 0.237 0.350 0.615 1.030 bs[2,13] 0.125 0.197 -0.274 -0.005 0.123 0.239 0.524 1.012 bs[2,14] 0.192 0.152 -0.101 0.094 0.195 0.295 0.482 1.013 bs[2,15] -0.119 0.237 -0.600 -0.261 -0.135 0.051 0.314 1.019 bs[2,16] -0.314 0.218 -0.774 -0.458 -0.311 -0.161 0.062 1.009 bs[2,17] 0.141 0.195 -0.271 0.011 0.137 0.276 0.525 1.003 bs[2,18] -0.122 0.176 -0.461 -0.234 -0.123 -0.015 0.234 1.000 bs[2,19] 0.570 0.205 0.122 0.432 0.586 0.707 0.948 1.047 bs[2,20] 0.124 0.193 -0.252 0.005 0.134 0.254 0.501 1.019 bs[2,21] -0.108 0.215 -0.546 -0.247 -0.113 0.041 0.289 1.003 bs[2,22] -0.374 0.190 -0.755 -0.504 -0.361 -0.241 -0.037 1.005 bs[2,23] 0.037 0.160 -0.288 -0.065 0.044 0.139 0.348 1.006 bs[2,24] 0.163 0.230 -0.277 0.010 0.164 0.310 0.595 1.012 bs[2,25] 0.084 0.195 -0.294 -0.040 0.074 0.221 0.460 1.004 bs[2,26] -0.183 0.191 -0.539 -0.312 -0.186 -0.050 0.203 1.005 bs[2,27] -0.554 0.266 -1.022 -0.734 -0.576 -0.389 0.029 1.065 bs[2,28] 0.137 0.195 -0.230 0.015 0.140 0.252 0.556 1.013 bs[2,29] 0.303 0.212 -0.121 0.163 0.304 0.451 0.691 1.012 bs[3,1] -0.111 0.143 -0.392 -0.208 -0.119 -0.023 0.187 1.065 bs[3,2] 0.023 0.131 -0.229 -0.054 0.021 0.107 0.283 1.048 bs[3,3] 0.054 0.130 -0.239 -0.020 0.053 0.134 0.291 1.082 bs[3,4] 0.114 0.184 -0.256 0.000 0.116 0.230 0.492 1.100 bs[3,5] 0.161 0.108 -0.029 0.086 0.159 0.234 0.377 1.002 bs[3,6] 0.386 0.134 0.111 0.306 0.388 0.470 0.641 1.008 bs[3,7] 0.074 0.126 -0.155 -0.014 0.071 0.160 0.325 1.037 bs[3,8] -0.744 0.121 -0.966 -0.829 -0.745 -0.670 -0.519 1.007 bs[3,9] -0.067 0.109 -0.280 -0.143 -0.060 0.010 0.129 1.020 bs[3,10] -0.197 0.128 -0.459 -0.283 -0.202 -0.112 0.063 1.008 bs[3,11] 0.120 0.196 -0.292 -0.007 0.143 0.254 0.461 1.109 bs[3,12] 0.135 0.141 -0.143 0.049 0.136 0.223 0.422 1.050 bs[3,13] -0.262 0.174 -0.594 -0.380 -0.258 -0.153 0.073 1.007 bs[3,14] -0.330 0.110 -0.554 -0.400 -0.331 -0.261 -0.095 1.057 bs[3,15] 0.160 0.164 -0.164 0.044 0.165 0.264 0.500 1.001 bs[3,16] 0.139 0.134 -0.117 0.048 0.144 0.223 0.408 1.001 bs[3,17] -0.005 0.135 -0.257 -0.099 -0.010 0.088 0.271 1.012 bs[3,18] -0.022 0.113 -0.233 -0.100 -0.019 0.052 0.193 1.006 bs[3,19] -0.249 0.122 -0.458 -0.337 -0.252 -0.164 -0.016 1.042 bs[3,20] -0.038 0.120 -0.259 -0.126 -0.032 0.048 0.193 1.005 bs[3,21] 0.086 0.146 -0.193 -0.002 0.078 0.179 0.379 1.009 bs[3,22] -0.115 0.121 -0.342 -0.196 -0.114 -0.039 0.134 1.005 bs[3,23] -0.050 0.104 -0.255 -0.122 -0.048 0.022 0.155 1.012 bs[3,24] 0.105 0.162 -0.219 0.003 0.105 0.211 0.420 1.004 bs[3,25] -0.134 0.150 -0.427 -0.243 -0.137 -0.036 0.160 1.048 bs[3,26] 0.085 0.127 -0.156 0.003 0.083 0.165 0.322 1.010 bs[3,27] 0.371 0.186 -0.022 0.258 0.375 0.503 0.726 1.034 bs[3,28] 0.188 0.133 -0.069 0.101 0.184 0.277 0.440 1.009 bs[3,29] -0.070 0.133 -0.318 -0.159 -0.070 0.016 0.201 1.009 bs[4,1] -0.133 0.058 -0.244 -0.172 -0.134 -0.093 -0.022 1.016 bs[4,2] -0.024 0.058 -0.141 -0.057 -0.026 0.015 0.088 0.999 bs[4,3] 0.035 0.049 -0.058 0.002 0.034 0.066 0.133 1.003 bs[4,4] -0.062 0.072 -0.217 -0.106 -0.062 -0.016 0.091 1.021 bs[4,5] 0.014 0.051 -0.079 -0.021 0.012 0.045 0.131 1.014 bs[4,6] 0.029 0.055 -0.075 -0.009 0.026 0.066 0.140 1.000 bs[4,7] -0.004 0.049 -0.092 -0.036 -0.008 0.028 0.096 1.006 bs[4,8] 0.099 0.053 -0.008 0.068 0.099 0.131 0.202 1.023 bs[4,9] -0.020 0.051 -0.126 -0.050 -0.019 0.010 0.081 1.028 bs[4,10] 0.060 0.059 -0.061 0.023 0.061 0.101 0.172 1.036 bs[4,11] 0.050 0.070 -0.088 0.003 0.053 0.096 0.178 1.030 bs[4,12] -0.034 0.058 -0.141 -0.072 -0.034 0.002 0.085 1.009 bs[4,13] 0.067 0.061 -0.054 0.024 0.067 0.110 0.183 1.013 bs[4,14] 0.122 0.051 0.018 0.088 0.123 0.155 0.218 1.001 bs[4,15] -0.033 0.075 -0.178 -0.085 -0.028 0.017 0.106 1.006 bs[4,16] -0.061 0.068 -0.195 -0.108 -0.059 -0.012 0.073 1.003 bs[4,17] 0.041 0.067 -0.104 0.000 0.043 0.085 0.172 1.000 bs[4,18] -0.094 0.062 -0.215 -0.136 -0.093 -0.052 0.017 1.001 bs[4,19] 0.034 0.052 -0.063 -0.003 0.036 0.069 0.136 1.017 bs[4,20] 0.056 0.062 -0.062 0.012 0.054 0.098 0.179 1.000 bs[4,21] 0.002 0.071 -0.131 -0.046 0.003 0.048 0.154 0.999 bs[4,22] -0.045 0.063 -0.163 -0.089 -0.046 -0.002 0.078 1.001 bs[4,23] -0.100 0.047 -0.191 -0.132 -0.101 -0.068 -0.011 1.000 bs[4,24] -0.088 0.068 -0.221 -0.134 -0.088 -0.044 0.051 1.009 bs[4,25] -0.076 0.060 -0.199 -0.117 -0.075 -0.036 0.035 1.004 bs[4,26] 0.100 0.065 -0.016 0.054 0.097 0.140 0.237 0.999 bs[4,27] -0.009 0.070 -0.153 -0.053 -0.008 0.036 0.119 1.005 bs[4,28] 0.020 0.067 -0.107 -0.028 0.021 0.061 0.158 1.000 bs[4,29] 0.058 0.070 -0.079 0.012 0.054 0.105 0.195 1.003 bs[5,1] -0.117 0.120 -0.338 -0.204 -0.124 -0.043 0.129 1.018 bs[5,2] -0.089 0.121 -0.336 -0.167 -0.086 -0.011 0.157 1.006 bs[5,3] -0.069 0.096 -0.247 -0.132 -0.068 -0.002 0.118 1.017 bs[5,4] 0.131 0.133 -0.145 0.042 0.131 0.214 0.388 1.023 bs[5,5] -0.016 0.091 -0.191 -0.075 -0.020 0.043 0.168 0.999 bs[5,6] -0.058 0.113 -0.271 -0.129 -0.056 0.014 0.159 1.011 bs[5,7] -0.086 0.105 -0.287 -0.157 -0.085 -0.024 0.126 1.002 bs[5,8] 0.129 0.102 -0.073 0.063 0.129 0.196 0.322 1.015 bs[5,9] 0.144 0.103 -0.087 0.082 0.145 0.210 0.343 1.046 bs[5,10] 0.169 0.118 -0.060 0.097 0.172 0.245 0.392 1.042 bs[5,11] -0.221 0.121 -0.449 -0.298 -0.216 -0.138 0.015 1.010 bs[5,12] 0.108 0.113 -0.097 0.028 0.108 0.181 0.346 1.001 bs[5,13] -0.102 0.117 -0.329 -0.179 -0.097 -0.025 0.107 1.000 bs[5,14] -0.113 0.093 -0.317 -0.169 -0.104 -0.052 0.068 1.003 bs[5,15] 0.119 0.146 -0.151 0.020 0.112 0.214 0.410 0.999 bs[5,16] -0.150 0.136 -0.450 -0.230 -0.143 -0.057 0.105 1.005 bs[5,17] 0.128 0.128 -0.117 0.041 0.124 0.217 0.373 1.003 bs[5,18] 0.111 0.122 -0.125 0.030 0.111 0.189 0.372 1.000 bs[5,19] 0.083 0.100 -0.118 0.017 0.085 0.146 0.283 1.004 bs[5,20] -0.091 0.122 -0.353 -0.154 -0.083 -0.017 0.149 1.024 bs[5,21] -0.078 0.135 -0.348 -0.164 -0.072 0.013 0.172 1.006 bs[5,22] -0.156 0.134 -0.419 -0.242 -0.156 -0.066 0.115 1.002 bs[5,23] 0.062 0.092 -0.114 0.000 0.065 0.127 0.250 1.000 bs[5,24] -0.152 0.144 -0.461 -0.236 -0.149 -0.054 0.107 1.010 bs[5,25] 0.076 0.120 -0.156 0.001 0.071 0.151 0.335 1.004 bs[5,26] 0.140 0.134 -0.109 0.058 0.136 0.217 0.425 1.003 bs[5,27] 0.191 0.147 -0.094 0.095 0.192 0.290 0.473 1.009 bs[5,28] -0.072 0.135 -0.343 -0.162 -0.073 0.020 0.186 1.000 bs[5,29] 0.059 0.136 -0.202 -0.030 0.058 0.147 0.339 0.999 bs[6,1] 0.060 0.146 -0.275 -0.024 0.071 0.155 0.331 1.011 bs[6,2] 0.117 0.143 -0.150 0.031 0.116 0.202 0.404 1.011 bs[6,3] 0.142 0.123 -0.101 0.068 0.146 0.216 0.403 1.020 bs[6,4] -0.177 0.212 -0.583 -0.317 -0.183 -0.048 0.282 1.017 bs[6,5] 0.071 0.123 -0.163 -0.011 0.069 0.147 0.324 1.023 bs[6,6] 0.048 0.144 -0.222 -0.049 0.037 0.140 0.349 1.012 bs[6,7] 0.006 0.129 -0.246 -0.077 0.007 0.087 0.268 1.013 bs[6,8] -0.298 0.114 -0.501 -0.373 -0.303 -0.227 -0.063 1.015 bs[6,9] -0.068 0.130 -0.329 -0.149 -0.064 0.006 0.192 1.009 bs[6,10] 0.410 0.149 0.093 0.328 0.408 0.507 0.681 1.014 bs[6,11] 0.170 0.230 -0.364 0.047 0.185 0.311 0.597 1.021 bs[6,12] -0.499 0.153 -0.790 -0.604 -0.502 -0.401 -0.210 1.008 bs[6,13] 0.481 0.183 0.129 0.348 0.475 0.606 0.849 1.016 bs[6,14] 0.257 0.119 0.030 0.175 0.264 0.337 0.478 1.000 bs[6,15] -0.122 0.195 -0.496 -0.255 -0.120 -0.006 0.265 1.004 bs[6,16] 0.085 0.170 -0.228 -0.033 0.083 0.199 0.432 1.005 bs[6,17] -0.305 0.160 -0.607 -0.412 -0.307 -0.202 0.015 1.000 bs[6,18] 0.106 0.143 -0.173 0.007 0.104 0.199 0.397 1.002 bs[6,19] -0.079 0.143 -0.335 -0.174 -0.086 0.014 0.202 1.024 bs[6,20] -0.077 0.165 -0.420 -0.186 -0.076 0.032 0.243 1.000 bs[6,21] 0.409 0.168 0.101 0.299 0.408 0.523 0.758 1.000 bs[6,22] 0.019 0.149 -0.260 -0.073 0.012 0.115 0.337 1.002 bs[6,23] 0.264 0.120 0.044 0.177 0.261 0.354 0.504 1.004 bs[6,24] -0.320 0.194 -0.695 -0.448 -0.314 -0.188 0.061 1.049 bs[6,25] 0.003 0.166 -0.307 -0.102 0.004 0.107 0.332 1.005 bs[6,26] -0.469 0.168 -0.795 -0.578 -0.465 -0.353 -0.160 1.004 bs[6,27] 0.006 0.203 -0.378 -0.126 0.009 0.145 0.419 1.013 bs[6,28] -0.005 0.170 -0.348 -0.117 -0.009 0.099 0.331 1.001 bs[6,29] -0.008 0.163 -0.323 -0.115 -0.012 0.095 0.327 1.001 log.conv12[1] -0.269 0.015 -0.297 -0.279 -0.268 -0.258 -0.240 1.003 log.conv12[2] -0.419 0.026 -0.469 -0.437 -0.418 -0.400 -0.374 1.001 tau[1] 6.233 0.394 5.452 5.964 6.226 6.517 6.963 0.999 tau[2] 5.603 0.344 4.970 5.365 5.590 5.830 6.267 1.000 tau[3] 20.549 1.685 17.390 19.405 20.510 21.662 24.050 1.004 tau[4] 19.065 1.086 17.089 18.357 19.045 19.682 21.421 1.013 tau[5] 7.173 0.540 6.212 6.821 7.140 7.528 8.287 1.014 tau[6] 5.676 0.277 5.178 5.489 5.653 5.856 6.233 1.004 tau.bs[1] 14.027 17.620 4.503 7.775 10.225 14.742 42.916 1.062 tau.bs[2] 12.274 6.746 4.715 8.100 10.845 14.137 28.680 1.061 tau.bs[3] 15.500 4.937 8.027 11.757 14.760 18.212 26.932 1.008 tau.bs[4] 127.167 50.084 55.258 92.600 119.900 153.550 237.537 1.013 tau.bs[5] 38.965 21.500 14.161 25.125 34.055 48.037 91.862 1.030 tau.bs[6] 12.835 4.556 5.739 9.792 12.050 15.527 22.091 1.005 tau.err[1] 1.152 0.622 0.385 0.694 1.064 1.417 2.831 1.125 tau.err[2] 1.430 0.192 1.069 1.298 1.408 1.546 1.829 1.056 tau.err[3] 1.001 0.970 0.029 0.285 0.734 1.413 3.321 1.001 tau.tol 18.094 30.770 1.604 3.979 8.339 18.285 98.626 1.245 tolerancy[1] 0.246 0.242 -0.128 0.071 0.217 0.380 0.791 1.060 tolerancy[2] 0.131 0.249 -0.275 -0.019 0.108 0.245 0.708 1.015 tolerancy[3] 0.100 0.230 -0.301 -0.054 0.080 0.225 0.613 1.040 tolerancy[4] -0.814 0.268 -1.367 -0.975 -0.829 -0.638 -0.314 1.038 tolerancy[5] -0.031 0.232 -0.491 -0.173 -0.032 0.104 0.431 1.065 tolerancy[6] -0.008 0.239 -0.430 -0.172 -0.026 0.131 0.504 1.035 tolerancy[7] 0.139 0.239 -0.269 -0.015 0.111 0.281 0.686 1.037 tolerancy[8] -0.115 0.294 -0.710 -0.300 -0.105 0.064 0.503 1.054 tolerancy[9] -0.314 0.266 -0.906 -0.460 -0.275 -0.139 0.122 1.126 tolerancy[10] -0.408 0.321 -1.173 -0.596 -0.365 -0.165 0.085 1.108 tolerancy[11] -0.877 0.298 -1.538 -1.042 -0.861 -0.700 -0.331 1.025 tolerancy[12] -0.133 0.264 -0.715 -0.293 -0.105 0.035 0.367 1.009 tolerancy[13] -0.820 0.375 -1.426 -1.083 -0.885 -0.614 0.046 1.025 tolerancy[14] -0.117 0.354 -0.904 -0.298 -0.085 0.085 0.545 1.048 tolerancy[15] 0.852 0.372 -0.022 0.687 0.902 1.080 1.504 1.025 tolerancy[16] 1.001 0.337 0.247 0.831 1.014 1.190 1.726 1.006 tolerancy[17] 0.782 0.403 -0.141 0.560 0.841 1.065 1.401 1.045 tolerancy[18] 0.890 0.321 0.185 0.688 0.928 1.101 1.431 1.021 tolerancy[19] 0.349 0.417 -0.293 0.054 0.281 0.575 1.335 1.083 tolerancy[20] 1.067 0.318 0.459 0.890 1.052 1.222 1.824 1.010 tolerancy[21] 1.003 0.320 0.338 0.815 0.997 1.184 1.668 1.008 tolerancy[22] 0.809 0.348 -0.015 0.624 0.842 1.022 1.467 1.031 tolerancy[23] 0.787 0.369 -0.065 0.589 0.824 1.024 1.425 1.023 tolerancy[24] -0.334 0.602 -1.150 -0.820 -0.473 0.055 1.081 1.123 tolerancy[25] 0.140 0.342 -0.499 -0.078 0.117 0.332 0.867 1.044 tolerancy[26] 0.821 0.349 0.063 0.612 0.856 1.038 1.466 1.030 tolerancy[27] -1.325 0.417 -2.366 -1.530 -1.260 -1.028 -0.726 1.052 tolerancy[28] 0.976 0.349 0.218 0.798 1.001 1.167 1.702 1.017 tolerancy[29] 1.084 0.323 0.484 0.885 1.064 1.251 1.806 1.043 deviance 13013.283 1064.255 10928.496 12390.000 12920.000 13642.499 15360.500 1.125 n.eff bb[1] 92 bb[2] 37 bb[3] 120 bb[4] 600 bb[5] 150 bb[6] 52 bc[1,1] 340 bc[1,2] 68 bc[1,3] 55 bc[1,4] 240 bc[1,5] 50 bc[2,1] 280 bc[2,2] 93 bc[2,3] 120 bc[2,4] 180 bc[2,5] 56 bc[3,1] 600 bc[3,2] 95 bc[3,3] 59 bc[3,4] 31 bc[3,5] 90 bc[4,1] 280 bc[4,2] 600 bc[4,3] 600 bc[4,4] 53 bc[4,5] 600 bc[5,1] 600 bc[5,2] 600 bc[5,3] 600 bc[5,4] 76 bc[5,5] 390 bc[6,1] 600 bc[6,2] 330 bc[6,3] 44 bc[6,4] 92 bc[6,5] 170 bs[1,1] 200 bs[1,2] 600 bs[1,3] 110 bs[1,4] 260 bs[1,5] 64 bs[1,6] 150 bs[1,7] 600 bs[1,8] 74 bs[1,9] 29 bs[1,10] 29 bs[1,11] 120 bs[1,12] 57 bs[1,13] 93 bs[1,14] 150 bs[1,15] 420 bs[1,16] 220 bs[1,17] 110 bs[1,18] 540 bs[1,19] 42 bs[1,20] 130 bs[1,21] 120 bs[1,22] 570 bs[1,23] 570 bs[1,24] 130 bs[1,25] 230 bs[1,26] 600 bs[1,27] 40 bs[1,28] 600 bs[1,29] 130 bs[2,1] 46 bs[2,2] 51 bs[2,3] 39 bs[2,4] 83 bs[2,5] 180 bs[2,6] 130 bs[2,7] 70 bs[2,8] 600 bs[2,9] 330 bs[2,10] 250 bs[2,11] 90 bs[2,12] 70 bs[2,13] 170 bs[2,14] 150 bs[2,15] 110 bs[2,16] 600 bs[2,17] 490 bs[2,18] 600 bs[2,19] 55 bs[2,20] 120 bs[2,21] 470 bs[2,22] 310 bs[2,23] 400 bs[2,24] 150 bs[2,25] 600 bs[2,26] 310 bs[2,27] 35 bs[2,28] 200 bs[2,29] 160 bs[3,1] 46 bs[3,2] 54 bs[3,3] 46 bs[3,4] 29 bs[3,5] 600 bs[3,6] 210 bs[3,7] 58 bs[3,8] 490 bs[3,9] 110 bs[3,10] 490 bs[3,11] 24 bs[3,12] 47 bs[3,13] 290 bs[3,14] 43 bs[3,15] 600 bs[3,16] 600 bs[3,17] 160 bs[3,18] 260 bs[3,19] 51 bs[3,20] 330 bs[3,21] 180 bs[3,22] 300 bs[3,23] 150 bs[3,24] 600 bs[3,25] 45 bs[3,26] 180 bs[3,27] 65 bs[3,28] 190 bs[3,29] 210 bs[4,1] 200 bs[4,2] 600 bs[4,3] 520 bs[4,4] 98 bs[4,5] 180 bs[4,6] 600 bs[4,7] 300 bs[4,8] 93 bs[4,9] 71 bs[4,10] 57 bs[4,11] 69 bs[4,12] 230 bs[4,13] 140 bs[4,14] 600 bs[4,15] 270 bs[4,16] 550 bs[4,17] 600 bs[4,18] 600 bs[4,19] 110 bs[4,20] 600 bs[4,21] 600 bs[4,22] 600 bs[4,23] 600 bs[4,24] 200 bs[4,25] 410 bs[4,26] 600 bs[4,27] 570 bs[4,28] 600 bs[4,29] 430 bs[5,1] 120 bs[5,2] 300 bs[5,3] 110 bs[5,4] 130 bs[5,5] 600 bs[5,6] 330 bs[5,7] 560 bs[5,8] 130 bs[5,9] 46 bs[5,10] 51 bs[5,11] 290 bs[5,12] 600 bs[5,13] 600 bs[5,14] 600 bs[5,15] 600 bs[5,16] 600 bs[5,17] 440 bs[5,18] 600 bs[5,19] 470 bs[5,20] 81 bs[5,21] 310 bs[5,22] 600 bs[5,23] 600 bs[5,24] 250 bs[5,25] 600 bs[5,26] 600 bs[5,27] 200 bs[5,28] 600 bs[5,29] 600 bs[6,1] 190 bs[6,2] 190 bs[6,3] 130 bs[6,4] 150 bs[6,5] 120 bs[6,6] 160 bs[6,7] 170 bs[6,8] 150 bs[6,9] 200 bs[6,10] 140 bs[6,11] 190 bs[6,12] 220 bs[6,13] 120 bs[6,14] 600 bs[6,15] 600 bs[6,16] 340 bs[6,17] 600 bs[6,18] 600 bs[6,19] 87 bs[6,20] 600 bs[6,21] 600 bs[6,22] 590 bs[6,23] 440 bs[6,24] 45 bs[6,25] 380 bs[6,26] 600 bs[6,27] 140 bs[6,28] 600 bs[6,29] 600 log.conv12[1] 490 log.conv12[2] 600 tau[1] 600 tau[2] 600 tau[3] 460 tau[4] 150 tau[5] 130 tau[6] 390 tau.bs[1] 48 tau.bs[2] 39 tau.bs[3] 210 tau.bs[4] 190 tau.bs[5] 68 tau.bs[6] 290 tau.err[1] 31 tau.err[2] 98 tau.err[3] 600 tau.tol 14 tolerancy[1] 41 tolerancy[2] 170 tolerancy[3] 74 tolerancy[4] 120 tolerancy[5] 37 tolerancy[6] 150 tolerancy[7] 130 tolerancy[8] 69 tolerancy[9] 21 tolerancy[10] 24 tolerancy[11] 600 tolerancy[12] 370 tolerancy[13] 110 tolerancy[14] 61 tolerancy[15] 140 tolerancy[16] 600 tolerancy[17] 63 tolerancy[18] 290 tolerancy[19] 30 tolerancy[20] 410 tolerancy[21] 530 tolerancy[22] 130 tolerancy[23] 270 tolerancy[24] 21 tolerancy[25] 60 tolerancy[26] 100 tolerancy[27] 57 tolerancy[28] 600 tolerancy[29] 150 deviance 57 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 = 4771.9 and DIC = 17785.0 DIC is an estimate of expected predictive error (lower deviance is better).