Inference for Bugs model at "/home/kubo/miyata/model2007/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 n.eff bb[1] -0.018 0.475 -0.937 -0.317 -0.030 0.283 0.864 1.002 600 bb[2] 1.428 0.230 1.001 1.259 1.420 1.592 1.871 1.013 140 bb[3] 1.069 0.135 0.744 1.001 1.073 1.151 1.320 1.032 290 bb[4] 0.275 0.042 0.190 0.245 0.274 0.301 0.354 1.012 220 bb[5] -0.461 0.058 -0.570 -0.501 -0.460 -0.429 -0.348 1.014 220 bb[6] -1.515 0.234 -1.941 -1.666 -1.532 -1.384 -0.994 1.149 24 bb[7] -0.485 0.050 -0.588 -0.518 -0.483 -0.451 -0.388 1.001 600 bb[8] 4.929 0.032 4.872 4.903 4.927 4.952 4.994 1.017 110 bb[9] -0.208 0.023 -0.256 -0.224 -0.207 -0.194 -0.166 1.006 260 bb[10] -8.466 0.047 -8.568 -8.494 -8.462 -8.428 -8.393 1.117 37 bb[11] 3.003 0.213 2.567 2.876 3.003 3.138 3.399 1.113 23 bb[12] -0.115 0.049 -0.210 -0.143 -0.112 -0.081 -0.030 1.004 400 bb[13] 1.412 0.093 1.231 1.349 1.414 1.467 1.609 1.012 210 bs[1,1] 0.024 0.354 -0.691 -0.154 0.011 0.168 0.789 1.019 320 bs[1,2] 0.125 0.256 -0.381 -0.052 0.135 0.313 0.577 1.018 120 bs[1,3] -0.139 0.145 -0.405 -0.233 -0.144 -0.056 0.171 1.022 310 bs[1,4] 0.093 0.079 -0.055 0.040 0.091 0.141 0.254 1.011 170 bs[1,5] -0.063 0.095 -0.248 -0.127 -0.063 0.001 0.123 1.036 58 bs[1,6] 0.643 0.244 0.099 0.506 0.656 0.803 1.076 1.139 24 bs[1,7] -0.119 0.092 -0.306 -0.176 -0.115 -0.056 0.052 1.001 600 bs[1,8] 0.098 0.041 0.011 0.074 0.099 0.126 0.178 1.008 280 bs[1,9] -0.037 0.032 -0.097 -0.060 -0.036 -0.015 0.027 1.021 96 bs[1,10] 0.091 0.072 -0.039 0.041 0.088 0.140 0.251 1.039 70 bs[1,11] -0.237 0.281 -0.842 -0.420 -0.200 -0.042 0.272 1.026 250 bs[1,12] 0.103 0.085 -0.043 0.045 0.102 0.153 0.289 1.001 600 bs[1,13] 0.122 0.142 -0.112 0.021 0.103 0.208 0.436 1.036 65 bs[2,1] 0.002 0.364 -0.732 -0.132 0.001 0.152 0.734 1.003 450 bs[2,2] -1.004 0.245 -1.512 -1.152 -1.005 -0.828 -0.550 1.012 180 bs[2,3] -0.510 0.154 -0.786 -0.601 -0.516 -0.422 -0.135 1.023 160 bs[2,4] -0.117 0.068 -0.246 -0.164 -0.116 -0.073 0.010 1.053 41 bs[2,5] -0.055 0.082 -0.214 -0.106 -0.054 -0.003 0.110 1.010 560 bs[2,6] -0.006 0.245 -0.556 -0.158 0.007 0.151 0.412 1.132 27 bs[2,7] -0.105 0.073 -0.242 -0.153 -0.105 -0.053 0.033 0.999 600 bs[2,8] 0.182 0.037 0.113 0.157 0.181 0.208 0.248 1.016 120 bs[2,9] 0.094 0.033 0.029 0.072 0.094 0.116 0.157 1.007 240 bs[2,10] 0.154 0.062 0.042 0.109 0.150 0.197 0.283 1.031 130 bs[2,11] 0.424 0.232 -0.030 0.277 0.425 0.560 0.904 1.139 19 bs[2,12] -0.035 0.082 -0.200 -0.088 -0.034 0.021 0.119 1.008 220 bs[2,13] -0.064 0.127 -0.358 -0.137 -0.050 0.025 0.159 1.031 79 bs[3,1] -0.001 0.330 -0.735 -0.151 -0.015 0.159 0.734 1.002 520 bs[3,2] -0.409 0.249 -0.904 -0.585 -0.400 -0.233 0.069 1.021 100 bs[3,3] -0.132 0.140 -0.387 -0.225 -0.139 -0.059 0.205 1.023 130 bs[3,4] -0.140 0.061 -0.265 -0.183 -0.137 -0.101 -0.023 1.032 68 bs[3,5] 0.120 0.091 -0.052 0.059 0.124 0.184 0.293 1.050 46 bs[3,6] -0.367 0.245 -0.913 -0.506 -0.357 -0.199 0.064 1.136 28 bs[3,7] 0.186 0.096 0.009 0.118 0.182 0.248 0.394 1.004 480 bs[3,8] -0.031 0.039 -0.111 -0.058 -0.031 -0.002 0.040 1.006 270 bs[3,9] 0.001 0.029 -0.058 -0.018 0.002 0.020 0.060 1.005 360 bs[3,10] -0.208 0.065 -0.324 -0.254 -0.213 -0.168 -0.077 1.027 96 bs[3,11] 0.527 0.267 0.025 0.348 0.515 0.685 1.093 1.094 31 bs[3,12] 0.135 0.074 -0.013 0.085 0.133 0.181 0.287 0.999 600 bs[3,13] -0.071 0.154 -0.420 -0.150 -0.051 0.029 0.169 1.014 180 bs[4,1] 0.010 0.387 -0.701 -0.155 0.000 0.149 0.768 1.011 600 bs[4,2] -0.538 0.253 -0.989 -0.715 -0.539 -0.370 -0.053 1.013 140 bs[4,3] -0.268 0.154 -0.540 -0.374 -0.275 -0.178 0.075 1.039 65 bs[4,4] 0.134 0.077 -0.006 0.086 0.128 0.179 0.302 1.142 19 bs[4,5] -0.176 0.121 -0.439 -0.250 -0.178 -0.095 0.055 1.099 26 bs[4,6] -0.409 0.251 -0.985 -0.554 -0.400 -0.241 0.048 1.129 28 bs[4,7] -0.118 0.098 -0.312 -0.180 -0.115 -0.053 0.069 1.000 600 bs[4,8] 0.131 0.041 0.049 0.101 0.131 0.162 0.207 1.015 130 bs[4,9] 0.031 0.037 -0.046 0.010 0.032 0.056 0.104 1.005 290 bs[4,10] 0.056 0.073 -0.086 0.004 0.061 0.104 0.204 1.006 600 bs[4,11] 0.091 0.258 -0.447 -0.048 0.102 0.259 0.574 1.052 42 bs[4,12] -0.035 0.085 -0.203 -0.088 -0.036 0.019 0.122 1.000 600 bs[4,13] 0.050 0.137 -0.187 -0.045 0.046 0.125 0.312 1.013 600 bs[5,1] 0.017 0.382 -0.777 -0.147 0.012 0.186 0.776 1.008 600 bs[5,2] -0.239 0.249 -0.695 -0.409 -0.238 -0.046 0.210 1.006 260 bs[5,3] 0.157 0.142 -0.113 0.072 0.151 0.226 0.476 1.028 96 bs[5,4] 0.067 0.075 -0.066 0.016 0.067 0.114 0.217 1.011 200 bs[5,5] -0.046 0.093 -0.238 -0.107 -0.046 0.019 0.127 1.024 82 bs[5,6] 0.735 0.246 0.150 0.595 0.740 0.894 1.195 1.136 25 bs[5,7] -0.127 0.090 -0.292 -0.191 -0.124 -0.063 0.041 1.004 600 bs[5,8] -0.035 0.041 -0.116 -0.062 -0.036 -0.007 0.045 1.008 220 bs[5,9] 0.001 0.039 -0.077 -0.023 0.001 0.027 0.074 1.005 360 bs[5,10] 0.679 0.078 0.540 0.626 0.679 0.731 0.837 1.023 600 bs[5,11] -0.921 0.283 -1.548 -1.090 -0.893 -0.739 -0.436 1.038 77 bs[5,12] -0.106 0.095 -0.288 -0.167 -0.107 -0.041 0.074 1.000 600 bs[5,13] 0.118 0.152 -0.149 0.022 0.105 0.200 0.447 1.018 110 bs[6,1] -0.003 0.374 -0.835 -0.157 -0.003 0.156 0.831 1.003 600 bs[6,2] 0.452 0.251 -0.055 0.281 0.458 0.634 0.929 1.019 100 bs[6,3] 0.259 0.158 -0.054 0.162 0.261 0.347 0.603 1.026 96 bs[6,4] -0.005 0.070 -0.146 -0.050 -0.006 0.039 0.130 1.000 600 bs[6,5] 0.129 0.099 -0.068 0.066 0.130 0.193 0.310 1.101 24 bs[6,6] -0.152 0.247 -0.773 -0.299 -0.142 0.014 0.293 1.122 29 bs[6,7] 0.015 0.090 -0.161 -0.041 0.016 0.074 0.190 1.004 600 bs[6,8] 0.001 0.042 -0.080 -0.028 0.001 0.029 0.084 1.014 130 bs[6,9] 0.017 0.035 -0.057 -0.005 0.017 0.040 0.083 0.999 600 bs[6,10] -0.252 0.078 -0.392 -0.311 -0.253 -0.203 -0.095 1.078 34 bs[6,11] -0.013 0.292 -0.608 -0.184 -0.009 0.161 0.573 1.065 37 bs[6,12] -0.050 0.083 -0.219 -0.101 -0.048 0.003 0.107 1.007 240 bs[6,13] -0.014 0.136 -0.286 -0.092 -0.010 0.065 0.243 1.007 490 bs[7,1] 0.006 0.411 -0.792 -0.149 0.015 0.155 0.804 1.015 600 bs[7,2] 2.241 0.255 1.744 2.071 2.230 2.419 2.746 1.017 120 bs[7,3] 1.113 0.281 0.579 0.921 1.122 1.286 1.709 1.021 170 bs[7,4] -0.064 0.076 -0.228 -0.110 -0.060 -0.014 0.082 1.006 260 bs[7,5] 0.233 0.105 0.038 0.162 0.232 0.304 0.450 1.008 210 bs[7,6] 1.521 0.293 0.935 1.327 1.527 1.711 2.082 1.104 38 bs[7,7] 0.129 0.097 -0.050 0.065 0.122 0.191 0.324 1.000 600 bs[7,8] -0.053 0.044 -0.138 -0.084 -0.052 -0.022 0.031 1.023 86 bs[7,9] -0.033 0.037 -0.105 -0.056 -0.036 -0.009 0.044 1.015 360 bs[7,10] -0.545 0.067 -0.670 -0.592 -0.549 -0.498 -0.412 1.037 110 bs[7,11] -0.914 0.367 -1.606 -1.161 -0.932 -0.693 -0.149 1.017 110 bs[7,12] -0.218 0.093 -0.414 -0.278 -0.214 -0.155 -0.050 1.002 600 bs[7,13] -0.091 0.143 -0.385 -0.171 -0.079 0.003 0.164 1.022 360 bs[8,1] -0.002 0.360 -0.679 -0.168 -0.003 0.157 0.714 1.004 600 bs[8,2] -0.893 0.255 -1.410 -1.071 -0.891 -0.719 -0.415 1.013 150 bs[8,3] -0.247 0.146 -0.515 -0.342 -0.259 -0.153 0.077 1.017 210 bs[8,4] -0.037 0.065 -0.157 -0.075 -0.036 0.003 0.095 1.009 200 bs[8,5] -0.088 0.093 -0.276 -0.142 -0.088 -0.024 0.083 1.096 25 bs[8,6] -0.923 0.249 -1.502 -1.083 -0.892 -0.757 -0.488 1.155 23 bs[8,7] -0.061 0.075 -0.199 -0.116 -0.062 -0.011 0.091 1.001 600 bs[8,8] 0.194 0.041 0.114 0.166 0.196 0.222 0.273 1.009 190 bs[8,9] -0.047 0.033 -0.116 -0.069 -0.047 -0.025 0.015 1.002 600 bs[8,10] -0.084 0.067 -0.224 -0.127 -0.081 -0.039 0.041 1.091 28 bs[8,11] 0.547 0.254 0.032 0.394 0.530 0.697 1.118 1.179 16 bs[8,12] 0.002 0.075 -0.147 -0.048 0.004 0.049 0.154 1.000 600 bs[8,13] -0.034 0.131 -0.317 -0.107 -0.024 0.046 0.203 1.030 75 bs[9,1] -0.016 0.348 -0.838 -0.164 -0.003 0.147 0.719 1.011 170 bs[9,2] 0.518 0.262 -0.007 0.338 0.536 0.703 1.021 1.015 130 bs[9,3] 0.027 0.165 -0.291 -0.076 0.021 0.130 0.389 1.024 120 bs[9,4] -0.010 0.074 -0.140 -0.063 -0.014 0.036 0.142 1.042 53 bs[9,5] -0.306 0.115 -0.551 -0.373 -0.295 -0.232 -0.093 1.026 110 bs[9,6] 0.361 0.259 -0.204 0.191 0.374 0.544 0.826 1.121 28 bs[9,7] -0.010 0.086 -0.184 -0.068 -0.008 0.048 0.157 1.000 600 bs[9,8] 0.003 0.042 -0.080 -0.025 0.003 0.030 0.086 1.010 170 bs[9,9] 0.007 0.037 -0.063 -0.017 0.007 0.035 0.078 1.002 600 bs[9,10] -0.065 0.083 -0.221 -0.125 -0.066 -0.012 0.119 1.050 46 bs[9,11] -0.093 0.291 -0.653 -0.273 -0.094 0.076 0.479 1.059 39 bs[9,12] 0.025 0.089 -0.152 -0.033 0.019 0.083 0.197 1.001 600 bs[9,13] -0.062 0.139 -0.395 -0.132 -0.048 0.025 0.176 1.005 300 bs[10,1] -0.014 0.373 -0.876 -0.156 -0.002 0.153 0.785 1.024 130 bs[10,2] 0.552 0.244 0.075 0.396 0.555 0.725 1.003 1.020 100 bs[10,3] 0.368 0.153 0.102 0.263 0.362 0.461 0.738 1.009 600 bs[10,4] 0.087 0.071 -0.045 0.040 0.085 0.133 0.234 1.014 140 bs[10,5] -0.159 0.098 -0.355 -0.220 -0.159 -0.096 0.042 1.002 600 bs[10,6] -1.161 0.257 -1.724 -1.328 -1.153 -0.989 -0.683 1.107 34 bs[10,7] 0.104 0.081 -0.041 0.048 0.105 0.159 0.271 1.000 600 bs[10,8] -0.168 0.040 -0.245 -0.194 -0.166 -0.140 -0.092 1.009 180 bs[10,9] 0.036 0.035 -0.028 0.010 0.037 0.061 0.099 1.002 600 bs[10,10] 0.204 0.076 0.055 0.151 0.205 0.257 0.356 1.036 66 bs[10,11] -0.098 0.278 -0.601 -0.284 -0.118 0.068 0.523 1.153 20 bs[10,12] 0.006 0.077 -0.142 -0.043 0.004 0.052 0.166 1.002 600 bs[10,13] -0.081 0.133 -0.366 -0.158 -0.070 0.006 0.162 1.061 40 bs[11,1] -0.004 0.348 -0.749 -0.139 0.004 0.152 0.713 1.003 600 bs[11,2] -0.711 0.246 -1.211 -0.878 -0.711 -0.528 -0.278 1.021 100 bs[11,3] -0.469 0.150 -0.745 -0.561 -0.473 -0.387 -0.109 1.050 47 bs[11,4] 0.078 0.065 -0.045 0.034 0.076 0.124 0.214 1.010 240 bs[11,5] 0.018 0.100 -0.172 -0.048 0.018 0.083 0.211 1.014 170 bs[11,6] -0.628 0.247 -1.154 -0.780 -0.616 -0.465 -0.156 1.139 25 bs[11,7] -0.009 0.092 -0.203 -0.066 -0.010 0.049 0.168 1.004 600 bs[11,8] -0.181 0.042 -0.259 -0.209 -0.179 -0.151 -0.101 1.003 460 bs[11,9] 0.007 0.033 -0.059 -0.015 0.007 0.029 0.074 1.003 410 bs[11,10] 0.138 0.077 -0.010 0.081 0.137 0.191 0.293 1.028 120 bs[11,11] 0.351 0.241 -0.113 0.198 0.345 0.512 0.838 1.062 37 bs[11,12] -0.046 0.077 -0.194 -0.098 -0.048 0.010 0.098 1.004 400 bs[11,13] -0.014 0.133 -0.294 -0.097 -0.006 0.072 0.235 1.008 500 bs[12,1] 0.037 0.383 -0.763 -0.131 0.019 0.174 0.993 1.000 600 bs[12,2] -0.246 0.246 -0.723 -0.406 -0.235 -0.082 0.237 1.007 250 bs[12,3] -0.049 0.148 -0.326 -0.143 -0.048 0.029 0.291 1.021 200 bs[12,4] -0.084 0.079 -0.236 -0.138 -0.084 -0.030 0.073 1.059 38 bs[12,5] 0.212 0.086 0.042 0.150 0.213 0.268 0.382 1.004 350 bs[12,6] 0.311 0.247 -0.257 0.171 0.309 0.480 0.748 1.124 29 bs[12,7] 0.124 0.089 -0.039 0.061 0.119 0.189 0.293 1.003 560 bs[12,8] -0.003 0.043 -0.084 -0.033 -0.001 0.027 0.077 1.012 150 bs[12,9] -0.043 0.038 -0.127 -0.067 -0.041 -0.017 0.027 1.004 600 bs[12,10] -0.161 0.069 -0.290 -0.206 -0.158 -0.114 -0.025 1.009 190 bs[12,11] -0.105 0.269 -0.657 -0.268 -0.090 0.052 0.438 1.045 51 bs[12,12] 0.194 0.095 0.029 0.127 0.190 0.252 0.388 1.007 290 bs[12,13] -0.034 0.130 -0.321 -0.100 -0.030 0.041 0.207 1.039 75 bs[13,1] -0.007 0.372 -0.873 -0.165 -0.006 0.170 0.788 1.002 510 bs[13,2] 0.044 0.270 -0.477 -0.145 0.045 0.232 0.577 1.020 95 bs[13,3] 0.029 0.156 -0.286 -0.068 0.028 0.114 0.411 1.025 140 bs[13,4] 0.022 0.088 -0.141 -0.035 0.020 0.071 0.210 1.017 110 bs[13,5] 0.092 0.089 -0.079 0.036 0.092 0.151 0.263 1.027 79 bs[13,6] -0.308 0.249 -0.947 -0.441 -0.286 -0.143 0.134 1.128 29 bs[13,7] 0.058 0.078 -0.080 0.005 0.054 0.110 0.225 1.000 600 bs[13,8] -0.105 0.053 -0.209 -0.140 -0.104 -0.070 -0.009 1.007 310 bs[13,9] -0.046 0.049 -0.147 -0.077 -0.042 -0.013 0.043 1.000 600 bs[13,10] 0.105 0.078 -0.048 0.050 0.108 0.166 0.243 1.005 600 bs[13,11] 0.082 0.264 -0.488 -0.071 0.096 0.246 0.574 1.026 85 bs[13,12] 0.070 0.119 -0.153 -0.009 0.065 0.148 0.303 1.002 600 bs[13,13] 0.081 0.121 -0.132 -0.001 0.072 0.150 0.352 1.054 48 tau.bs[1] 37.042 54.840 1.082 5.727 17.330 45.212 205.417 0.999 600 tau.bs[2] 1.413 0.551 0.500 1.005 1.339 1.777 2.657 0.999 600 tau.bs[3] 5.839 3.073 1.749 3.618 5.258 7.311 13.053 1.002 600 tau.bs[4] 83.271 48.840 20.608 48.830 74.125 106.225 205.521 1.012 170 tau.bs[5] 32.135 16.745 9.417 19.605 29.650 40.372 71.654 1.008 240 tau.bs[6] 1.837 0.804 0.655 1.279 1.682 2.303 3.873 1.006 600 tau.bs[7] 61.023 41.991 15.950 33.282 50.635 73.852 175.312 1.005 490 tau.bs[8] 60.917 27.117 22.039 41.845 56.790 74.577 125.545 1.003 580 tau.bs[9] 242.858 110.462 77.515 159.775 231.750 305.400 487.405 1.001 600 tau.bs[10] 12.028 5.068 4.296 8.590 11.390 14.802 24.551 0.999 600 tau.bs[11] 4.058 2.341 1.091 2.449 3.509 5.194 9.896 1.007 360 tau.bs[12] 59.902 37.844 16.073 34.640 51.135 72.955 153.462 1.001 600 tau.bs[13] 72.081 67.246 9.202 27.889 48.500 96.522 245.222 1.026 78 tau[1] 4.616 1.100 2.919 3.900 4.430 5.164 7.507 1.009 200 tau[2] 2.361 0.144 2.085 2.263 2.363 2.455 2.661 1.007 240 tau[3] 24569.583 1602.506 21498.498 23470.000 24550.000 25690.000 27670.250 1.022 100 tau[4] 52.469 6.239 42.726 47.795 51.785 56.532 66.280 1.006 320 tau[5] 7.599 0.523 6.726 7.217 7.588 7.924 8.782 1.004 600 tau[6] 402.813 24.570 355.590 384.975 402.650 420.925 451.302 1.000 600 tau[7] 10.685 0.869 9.048 10.100 10.640 11.240 12.441 1.067 35 tau[8] 4.002 0.268 3.548 3.811 3.981 4.184 4.538 1.002 600 tau[9] 6.644 0.485 5.730 6.302 6.631 6.953 7.616 0.999 600 deviance -17478.317 170.524 -17780.000 -17600.000 -17480.000 -17370.000 -17130.000 1.002 500 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 = 2316.2 and DIC = -15162.0 DIC is an estimate of expected predictive error (lower deviance is better).