Cl[1] 0.02178 0.002043 2.67E-5 0.01773 0.02178 0.02578 20000 180001 Cl[2] 0.04444 0.002814 1.918E-5 0.03913 0.04439 0.05012 20000 180001 Cl[3] 0.04172 0.00271 2.08E-5 0.03654 0.04167 0.0472 20000 180001 Cl[4] 0.03856 0.002615 2.093E-5 0.03357 0.03852 0.04378 20000 180001 Cl[5] 0.0429 0.002961 2.33E-5 0.0372 0.04284 0.04885 20000 180001 Cl[6] 0.04858 0.003257 2.504E-5 0.04234 0.04853 0.0551 20000 180001 Cl[7] 0.04911 0.003435 2.804E-5 0.04248 0.04906 0.05603 20000 180001 Cl[8] 0.04405 0.003074 2.48E-5 0.03815 0.04399 0.05026 20000 180001 Cl[9] 0.03151 0.00218 1.83E-5 0.02735 0.0315 0.03588 20000 180001 Cl[10] 0.0334 0.002653 2.615E-5 0.02827 0.03338 0.03866 20000 180001 Cl[11] 0.05461 0.00351 2.632E-5 0.04792 0.05458 0.06164 20000 180001 Cl[12] 0.04227 0.002758 1.963E-5 0.03702 0.04223 0.04789 20000 180001 Clmed 0.04012 0.003636 1.178E-5 0.03337 0.03997 0.04779 20000 180001 D[1,1] 0.05288 0.03096 2.14E-4 0.01877 0.0453 0.1315 20000 180001 D[1,2] -0.0227 0.06644 3.552E-4 -0.1698 -0.01712 0.09426 20000 180001 D[1,3] 0.03673 0.03164 2.221E-4 -0.003713 0.03028 0.1154 20000 180001 D[2,1] -0.0227 0.06644 3.552E-4 -0.1698 -0.01712 0.09426 20000 180001 D[2,2] 0.5548 0.3304 0.001648 0.1914 0.4742 1.395 20000 180001 D[2,3] -0.02246 0.08231 3.113E-4 -0.1994 -0.0183 0.1315 20000 180001 D[3,1] 0.03673 0.03164 2.221E-4 -0.003713 0.03028 0.1154 20000 180001 D[3,2] -0.02246 0.08231 3.113E-4 -0.1994 -0.0183 0.1315 20000 180001 D[3,3] 0.09266 0.04971 2.206E-4 0.03661 0.08083 0.219 20000 180001 beta[1] -2.434 0.0749 4.411E-4 -2.584 -2.433 -2.287 20000 180001 beta[2] 0.2639 0.2255 8.824E-4 -0.1753 0.2599 0.7237 20000 180001 beta[3] -3.22 0.09038 2.969E-4 -3.4 -3.22 -3.041 20000 180001 fitted[1,1] 1.204 0.1245 7.61E-4 0.9651 1.202 1.451 20000 180001 fitted[1,2] 1.811 0.09626 4.969E-4 1.621 1.812 1.997 20000 180001 fitted[1,3] 2.15 0.0694 2.97E-4 2.013 2.15 2.285 20000 180001 fitted[1,4] 2.279 0.06568 4.466E-4 2.15 2.279 2.408 20000 180001 fitted[1,5] 2.236 0.07355 5.561E-4 2.092 2.235 2.381 20000 180001 fitted[1,6] 2.163 0.07214 5.106E-4 2.023 2.162 2.306 20000 180001 fitted[1,7] 2.045 0.06814 4.447E-4 1.912 2.044 2.181 20000 180001 fitted[1,8] 1.92 0.06638 4.698E-4 1.79 1.92 2.051 20000 180001 fitted[1,9] 1.729 0.07103 6.787E-4 1.589 1.729 1.869 20000 180001 fitted[1,10] 0.9682 0.1419 0.001979 0.6904 0.969 1.248 20000 180001 fitted[2,1] 1.083 0.1131 6.164E-4 0.8634 1.082 1.308 20000 180001 fitted[2,2] 1.57 0.09458 4.518E-4 1.384 1.57 1.755 20000 180001 fitted[2,3] 1.924 0.07223 2.63E-4 1.781 1.925 2.065 20000 180001 fitted[2,4] 2.079 0.06531 3.48E-4 1.949 2.08 2.207 20000 180001 fitted[2,5] 2.009 0.07298 4.936E-4 1.866 2.01 2.152 20000 180001 fitted[2,6] 1.87 0.07191 4.855E-4 1.73 1.87 2.013 20000 180001 fitted[2,7] 1.671 0.06712 4.348E-4 1.541 1.67 1.804 20000 180001 fitted[2,8] 1.472 0.06498 4.165E-4 1.347 1.472 1.601 20000 180001 fitted[2,9] 1.17 0.07008 4.859E-4 1.033 1.17 1.307 20000 180001 fitted[2,10] -0.07022 0.1504 0.001277 -0.3702 -0.06959 0.2206 20000 180001 fitted[3,1] 1.451 0.133 7.785E-4 1.195 1.448 1.719 20000 180001 fitted[3,2] 1.911 0.09074 4.229E-4 1.729 1.913 2.086 20000 180001 fitted[3,3] 2.102 0.0671 2.822E-4 1.969 2.102 2.233 20000 180001 fitted[3,4] 2.132 0.07232 4.86E-4 1.988 2.133 2.272 20000 180001 fitted[3,5] 2.006 0.07344 5.173E-4 1.864 2.005 2.152 20000 180001 fitted[3,6] 1.874 0.06856 4.719E-4 1.741 1.873 2.011 20000 180001 fitted[3,7] 1.692 0.06343 4.28E-4 1.569 1.692 1.818 20000 180001 fitted[3,8] 1.516 0.0622 4.299E-4 1.394 1.515 1.638 20000 180001 fitted[3,9] 1.228 0.0687 5.245E-4 1.093 1.227 1.363 20000 180001 fitted[3,10] 0.1286 0.1434 0.001273 -0.1557 0.1291 0.4074 20000 180001 fitted[4,1] 1.013 0.1083 5.968E-4 0.8049 1.012 1.231 20000 180001 fitted[4,2] 1.435 0.09548 4.803E-4 1.248 1.434 1.624 20000 180001 fitted[4,3] 1.802 0.07723 3.131E-4 1.648 1.802 1.953 20000 180001 fitted[4,4] 2.056 0.06227 2.786E-4 1.934 2.056 2.178 20000 180001 fitted[4,5] 2.07 0.06794 4.497E-4 1.935 2.071 2.202 20000 180001 fitted[4,6] 1.978 0.07324 5.3E-4 1.835 1.978 2.122 20000 180001 fitted[4,7] 1.811 0.07293 5.329E-4 1.67 1.81 1.957 20000 180001 fitted[4,8] 1.631 0.07071 5.155E-4 1.494 1.63 1.772 20000 180001 fitted[4,9] 1.359 0.07242 5.521E-4 1.218 1.358 1.502 20000 180001 fitted[4,10] 0.1897 0.1492 0.001368 -0.1062 0.1903 0.4772 20000 180001 fitted[5,1] 1.151 0.1087 6.068E-4 0.9413 1.15 1.367 20000 180001 fitted[5,2] 1.583 0.09575 4.876E-4 1.396 1.583 1.771 20000 180001 fitted[5,3] 1.992 0.07533 3.012E-4 1.842 1.993 2.139 20000 180001 fitted[5,4] 2.232 0.06282 3.192E-4 2.109 2.232 2.355 20000 180001 fitted[5,5] 2.226 0.0701 5.0E-4 2.088 2.226 2.362 20000 180001 fitted[5,6] 2.123 0.0729 5.452E-4 1.981 2.122 2.267 20000 180001 fitted[5,7] 1.956 0.07035 5.192E-4 1.82 1.955 2.096 20000 180001 fitted[5,8] 1.774 0.06784 4.927E-4 1.643 1.773 1.909 20000 180001 fitted[5,9] 1.519 0.07074 5.307E-4 1.381 1.519 1.658 20000 180001 fitted[5,10] 0.4306 0.1448 0.00129 0.1456 0.431 0.7134 20000 180001 fitted[6,1] 0.5207 0.1105 6.456E-4 0.3079 0.5191 0.7409 20000 180001 fitted[6,2] 1.132 0.09397 4.951E-4 0.9476 1.131 1.316 20000 180001 fitted[6,3] 1.549 0.0731 3.036E-4 1.405 1.55 1.692 20000 180001 fitted[6,4] 1.744 0.06245 2.868E-4 1.621 1.744 1.866 20000 180001 fitted[6,5] 1.751 0.06866 4.616E-4 1.614 1.751 1.883 20000 180001 fitted[6,6] 1.656 0.07231 5.187E-4 1.514 1.656 1.798 20000 180001 fitted[6,7] 1.485 0.07077 5.05E-4 1.348 1.484 1.625 20000 180001 fitted[6,8] 1.282 0.06819 4.792E-4 1.151 1.281 1.417 20000 180001 fitted[6,9] 1.015 0.07123 5.261E-4 0.8767 1.014 1.155 20000 180001 fitted[6,10] -0.07658 0.1454 0.001318 -0.3647 -0.07566 0.2079 20000 180001 fitted[7,1] 0.2217 0.0994 6.48E-4 0.0308 0.2204 0.4217 20000 180001 fitted[7,2] 0.8326 0.09159 5.528E-4 0.6554 0.8317 1.015 20000 180001 fitted[7,3] 1.378 0.07818 3.829E-4 1.226 1.378 1.533 20000 180001 fitted[7,4] 1.755 0.06349 2.294E-4 1.631 1.756 1.881 20000 180001 fitted[7,5] 1.887 0.06222 3.938E-4 1.763 1.887 2.007 20000 180001 fitted[7,6] 1.858 0.06887 5.541E-4 1.721 1.859 1.99 20000 180001 fitted[7,7] 1.734 0.07455 6.371E-4 1.588 1.734 1.879 20000 180001 fitted[7,8] 1.568 0.07596 6.346E-4 1.421 1.568 1.719 20000 180001 fitted[7,9] 1.293 0.07733 6.106E-4 1.143 1.292 1.447 20000 180001 fitted[7,10] 0.1472 0.1504 0.001507 -0.1513 0.1481 0.439 20000 180001 fitted[8,1] 0.9331 0.1204 6.961E-4 0.7 0.9316 1.175 20000 180001 fitted[8,2] 1.477 0.09692 4.85E-4 1.285 1.477 1.667 20000 180001 fitted[8,3] 1.815 0.0724 2.822E-4 1.67 1.815 1.956 20000 180001 fitted[8,4] 1.975 0.06665 4.225E-4 1.843 1.975 2.104 20000 180001 fitted[8,5] 1.914 0.07432 5.503E-4 1.767 1.914 2.058 20000 180001 fitted[8,6] 1.795 0.0727 5.281E-4 1.655 1.795 1.939 20000 180001 fitted[8,7] 1.62 0.0675 4.634E-4 1.489 1.619 1.753 20000 180001 fitted[8,8] 1.457 0.0653 4.429E-4 1.33 1.457 1.586 20000 180001 fitted[8,9] 1.201 0.06964 5.209E-4 1.064 1.201 1.337 20000 180001 fitted[8,10] 0.1834 0.1424 0.001366 -0.09982 0.1846 0.4592 20000 180001 fitted[9,1] 1.835 0.1307 8.189E-4 1.564 1.841 2.074 20000 180001 fitted[9,2] 2.011 0.0721 3.321E-4 1.866 2.012 2.15 20000 180001 fitted[9,3] 2.021 0.06979 3.81E-4 1.884 2.022 2.157 20000 180001 fitted[9,4] 1.951 0.06944 4.039E-4 1.816 1.95 2.089 20000 180001 fitted[9,5] 1.825 0.06371 3.597E-4 1.702 1.825 1.952 20000 180001 fitted[9,6] 1.701 0.05938 3.364E-4 1.586 1.701 1.819 20000 180001 fitted[9,7] 1.522 0.05685 3.548E-4 1.411 1.521 1.634 20000 180001 fitted[9,8] 1.386 0.05819 4.051E-4 1.272 1.386 1.5 20000 180001 fitted[9,9] 1.152 0.06638 5.36E-4 1.022 1.152 1.282 20000 180001 fitted[9,10] 0.08183 0.146 0.001335 -0.2046 0.08283 0.3678 20000 180001 fitted[10,1] 1.076 0.1091 7.332E-4 0.868 1.074 1.297 20000 180001 fitted[10,2] 1.653 0.09122 5.343E-4 1.476 1.652 1.834 20000 180001 fitted[10,3] 1.84 0.08215 4.301E-4 1.679 1.84 2.002 20000 180001 fitted[10,4] 2.175 0.06224 2.521E-4 2.053 2.175 2.297 20000 180001 fitted[10,5] 2.26 0.06529 4.548E-4 2.13 2.262 2.387 20000 180001 fitted[10,6] 2.213 0.07278 5.721E-4 2.069 2.214 2.355 20000 180001 fitted[10,7] 2.089 0.07558 5.873E-4 1.941 2.088 2.239 20000 180001 fitted[10,8] 1.923 0.07407 5.477E-4 1.779 1.922 2.07 20000 180001 fitted[10,9] 1.717 0.07469 5.733E-4 1.571 1.717 1.864 20000 180001 fitted[10,10] 0.8294 0.1398 0.001575 0.5529 0.8301 1.101 20000 180001 fitted[11,1] 1.55 0.1386 8.277E-4 1.282 1.548 1.829 20000 180001 fitted[11,2] 1.897 0.08794 3.999E-4 1.718 1.899 2.064 20000 180001 fitted[11,3] 2.039 0.06898 3.67E-4 1.902 2.04 2.174 20000 180001 fitted[11,4] 1.996 0.07712 5.356E-4 1.845 1.996 2.148 20000 180001 fitted[11,5] 1.845 0.07219 5.021E-4 1.705 1.843 1.989 20000 180001 fitted[11,6] 1.708 0.06685 4.581E-4 1.578 1.707 1.841 20000 180001 fitted[11,7] 1.514 0.06231 4.275E-4 1.393 1.513 1.638 20000 180001 fitted[11,8] 1.321 0.06223 4.428E-4 1.199 1.32 1.444 20000 180001 fitted[11,9] 1.023 0.07056 5.439E-4 0.8853 1.022 1.162 20000 180001 fitted[11,10] -0.1311 0.1487 0.00126 -0.4224 -0.1311 0.1605 20000 180001 fitted[12,1] 0.6756 0.1018 6.338E-4 0.481 0.6737 0.8796 20000 180001 fitted[12,2] 1.273 0.09266 5.308E-4 1.095 1.272 1.457 20000 180001 fitted[12,3] 1.781 0.07794 3.611E-4 1.629 1.781 1.934 20000 180001 fitted[12,4] 2.125 0.06316 2.536E-4 2.002 2.125 2.249 20000 180001 fitted[12,5] 2.21 0.06516 4.527E-4 2.081 2.211 2.336 20000 180001 fitted[12,6] 2.14 0.07213 5.85E-4 1.996 2.141 2.279 20000 180001 fitted[12,7] 1.976 0.07525 6.197E-4 1.829 1.976 2.124 20000 180001 fitted[12,8] 1.788 0.07437 5.83E-4 1.645 1.788 1.936 20000 180001 fitted[12,9] 1.484 0.07505 5.399E-4 1.337 1.483 1.632 20000 180001 fitted[12,10] 0.2381 0.1535 0.001392 -0.06724 0.2386 0.5374 20000 180001 ka[1] 1.426 0.2821 0.002492 0.9672 1.394 2.07 20000 180001 ka[2] 1.349 0.2395 0.001895 0.9507 1.325 1.885 20000 180001 ka[3] 2.199 0.5269 0.003993 1.415 2.121 3.448 20000 180001 ka[4] 0.9026 0.1597 0.001289 0.6346 0.8868 1.256 20000 180001 ka[5] 1.053 0.1824 0.001501 0.7492 1.035 1.461 20000 180001 ka[6] 0.9524 0.1641 0.001339 0.6756 0.9374 1.32 20000 180001 ka[7] 0.5793 0.09612 9.967E-4 0.4131 0.5711 0.7895 20000 180001 ka[8] 1.435 0.2765 0.002268 0.9831 1.403 2.067 20000 180001 ka[9] 5.853 3.364 0.02483 2.86 5.132 12.94 20000 180001 ka[10] 0.7457 0.1407 0.001381 0.5113 0.7318 1.063 20000 180001 ka[11] 3.377 1.012 0.007478 2.031 3.199 5.809 20000 180001 ka[12] 0.6811 0.1129 0.001093 0.4882 0.6712 0.9269 20000 180001 ke[1] 0.06212 0.008176 1.154E-4 0.0463 0.06203 0.07852 20000 180001 ke[2] 0.1008 0.008905 7.785E-5 0.08389 0.1006 0.1189 20000 180001 ke[3] 0.09143 0.008311 7.409E-5 0.07538 0.09135 0.108 20000 180001 ke[4] 0.09229 0.009156 8.549E-5 0.07494 0.0921 0.1109 20000 180001 ke[5] 0.08813 0.008754 8.079E-5 0.07126 0.08799 0.1056 20000 180001 ke[6] 0.09291 0.009237 8.678E-5 0.07546 0.09271 0.1115 20000 180001 ke[7] 0.09461 0.01063 1.195E-4 0.07461 0.09427 0.1165 20000 180001 ke[8] 0.08466 0.008515 8.473E-5 0.06815 0.08455 0.1018 20000 180001 ke[9] 0.08342 0.00781 6.81E-5 0.06806 0.08334 0.09871 20000 180001 ke[10] 0.07662 0.009513 1.141E-4 0.0586 0.07637 0.09604 20000 180001 ke[11] 0.09647 0.008451 7.095E-5 0.08005 0.09643 0.1133 20000 180001 ke[12] 0.1031 0.01054 1.081E-4 0.08344 0.1028 0.1246 20000 180001 kemed 0.08795 0.006587 3.849E-5 0.07544 0.08778 0.1016 20000 180001 resid[1,1] -0.1598 0.1245 7.61E-4 -0.407 -0.1583 0.07872 20000 180001 resid[1,2] 0.0717 0.09626 4.969E-4 -0.1142 0.07087 0.2614 20000 180001 resid[1,3] 0.2013 0.0694 2.97E-4 0.06592 0.2011 0.3382 20000 180001 resid[1,4] -0.01106 0.06568 4.466E-4 -0.14 -0.01122 0.1181 20000 180001 resid[1,5] -0.08636 0.07355 5.561E-4 -0.2313 -0.08603 0.0577 20000 180001 resid[1,6] -0.0396 0.07214 5.106E-4 -0.183 -0.03872 0.09998 20000 180001 resid[1,7] -0.03414 0.06814 4.447E-4 -0.1698 -0.03351 0.09849 20000 180001 resid[1,8] 0.01027 0.06638 4.698E-4 -0.1208 0.01043 0.1402 20000 180001 resid[1,9] 0.05257 0.07103 6.787E-4 -0.087 0.05224 0.193 20000 180001 resid[1,10] 0.2197 0.1419 0.001979 -0.05985 0.2188 0.4974 20000 180001 resid[2,1] -0.5405 0.1131 6.164E-4 -0.7654 -0.5393 -0.3211 20000 180001 resid[2,2] 0.4979 0.09458 4.518E-4 0.313 0.4977 0.6845 20000 180001 resid[2,3] 0.1931 0.07223 2.63E-4 0.0525 0.1926 0.3365 20000 180001 resid[2,4] 0.04078 0.06531 3.48E-4 -0.08666 0.04036 0.1708 20000 180001 resid[2,5] -0.08522 0.07298 4.936E-4 -0.2278 -0.08545 0.05853 20000 180001 resid[2,6] -0.06526 0.07191 4.855E-4 -0.2084 -0.0645 0.07462 20000 180001 resid[2,7] 0.01577 0.06712 4.348E-4 -0.1181 0.01658 0.1459 20000 180001 resid[2,8] 0.04273 0.06498 4.165E-4 -0.08568 0.04335 0.1684 20000 180001 resid[2,9] -0.06804 0.07008 4.859E-4 -0.2053 -0.06759 0.06853 20000 180001 resid[2,10] -0.03514 0.1504 0.001277 -0.326 -0.03577 0.2648 20000 180001 resid[3,1] 0.03093 0.133 7.785E-4 -0.2376 0.03316 0.2861 20000 180001 resid[3,2] 0.02046 0.09074 4.229E-4 -0.1542 0.01885 0.2023 20000 180001 resid[3,3] 0.002523 0.0671 2.822E-4 -0.1287 0.002158 0.1349 20000 180001 resid[3,4] -0.07761 0.07232 4.86E-4 -0.2175 -0.07839 0.06587 20000 180001 resid[3,5] 0.008993 0.07344 5.173E-4 -0.137 0.009548 0.151 20000 180001 resid[3,6] -0.04926 0.06856 4.719E-4 -0.1864 -0.04846 0.08316 20000 180001 resid[3,7] -0.02432 0.06343 4.28E-4 -0.1505 -0.02384 0.09919 20000 180001 resid[3,8] 0.07365 0.0622 4.299E-4 -0.049 0.07379 0.1954 20000 180001 resid[3,9] 0.08074 0.0687 5.245E-4 -0.05437 0.08089 0.2153 20000 180001 resid[3,10] -0.07984 0.1434 0.001273 -0.3586 -0.08031 0.2045 20000 180001 resid[4,1] -0.3768 0.1083 5.968E-4 -0.5939 -0.3752 -0.1683 20000 180001 resid[4,2] 0.09128 0.09548 4.803E-4 -0.09785 0.09197 0.2776 20000 180001 resid[4,3] 0.3502 0.07723 3.131E-4 0.1992 0.3498 0.5033 20000 180001 resid[4,4] 0.06986 0.06227 2.786E-4 -0.0524 0.06964 0.1923 20000 180001 resid[4,5] -0.04995 0.06794 4.497E-4 -0.1814 -0.05082 0.08496 20000 180001 resid[4,6] -0.04918 0.07324 5.3E-4 -0.1931 -0.04941 0.09397 20000 180001 resid[4,7] -0.05637 0.07293 5.329E-4 -0.2023 -0.05564 0.08462 20000 180001 resid[4,8] 0.04282 0.07071 5.155E-4 -0.09901 0.04363 0.179 20000 180001 resid[4,9] 0.07399 0.07242 5.521E-4 -0.06958 0.07455 0.2149 20000 180001 resid[4,10] -0.04992 0.1492 0.001368 -0.3374 -0.05057 0.2459 20000 180001 resid[5,1] -0.4482 0.1087 6.068E-4 -0.6635 -0.4468 -0.2382 20000 180001 resid[5,2] 0.1451 0.09575 4.876E-4 -0.04339 0.1454 0.3326 20000 180001 resid[5,3] 0.4416 0.07533 3.012E-4 0.295 0.4409 0.5912 20000 180001 resid[5,4] 0.001635 0.06282 3.192E-4 -0.1222 0.001516 0.1247 20000 180001 resid[5,5] -0.0578 0.0701 5.0E-4 -0.1946 -0.05812 0.08032 20000 180001 resid[5,6] -0.09979 0.0729 5.452E-4 -0.244 -0.09948 0.04227 20000 180001 resid[5,7] 0.00302 0.07035 5.192E-4 -0.1373 0.004023 0.1388 20000 180001 resid[5,8] 7.728E-4 0.06784 4.927E-4 -0.1342 0.001565 0.1323 20000 180001 resid[5,9] -0.04424 0.07074 5.307E-4 -0.1837 -0.04423 0.09353 20000 180001 resid[5,10] 0.02045 0.1448 0.00129 -0.2623 0.02006 0.3055 20000 180001 resid[6,1] -0.266 0.1105 6.456E-4 -0.4863 -0.2645 -0.05322 20000 180001 resid[6,2] -0.006722 0.09397 4.951E-4 -0.1915 -0.005996 0.1773 20000 180001 resid[6,3] 0.3132 0.0731 3.036E-4 0.1707 0.313 0.4571 20000 180001 resid[6,4] 0.09991 0.06245 2.868E-4 -0.02268 0.09991 0.2224 20000 180001 resid[6,5] -0.04052 0.06866 4.616E-4 -0.1733 -0.0413 0.09609 20000 180001 resid[6,6] -0.05854 0.07231 5.187E-4 -0.2002 -0.05883 0.08302 20000 180001 resid[6,7] -0.09327 0.07077 5.05E-4 -0.2338 -0.09261 0.04333 20000 180001 resid[6,8] -0.04047 0.06819 4.792E-4 -0.1762 -0.03967 0.0906 20000 180001 resid[6,9] 0.007491 0.07123 5.261E-4 -0.1328 0.008006 0.1458 20000 180001 resid[6,10] -0.006806 0.1454 0.001318 -0.2913 -0.007725 0.2813 20000 180001 resid[7,1] -0.3843 0.0994 6.48E-4 -0.5842 -0.3829 -0.1933 20000 180001 resid[7,2] 0.02186 0.09159 5.528E-4 -0.1609 0.02268 0.199 20000 180001 resid[7,3] 0.2351 0.07818 3.829E-4 0.08059 0.2353 0.3878 20000 180001 resid[7,4] 0.1286 0.06349 2.294E-4 0.003294 0.1285 0.2528 20000 180001 resid[7,5] 0.07213 0.06222 3.938E-4 -0.04877 0.07147 0.1954 20000 180001 resid[7,6] 0.03775 0.06887 5.541E-4 -0.09438 0.03674 0.1752 20000 180001 resid[7,7] -0.0757 0.07455 6.371E-4 -0.2209 -0.07611 0.07066 20000 180001 resid[7,8] -0.08889 0.07596 6.346E-4 -0.2396 -0.08852 0.05822 20000 180001 resid[7,9] -0.03171 0.07733 6.106E-4 -0.1859 -0.03104 0.1184 20000 180001 resid[7,10] -0.007475 0.1504 0.001507 -0.2992 -0.008364 0.2911 20000 180001 resid[8,1] 0.182 0.1204 6.961E-4 -0.05962 0.1835 0.4151 20000 180001 resid[8,2] -0.3616 0.09692 4.85E-4 -0.5521 -0.362 -0.1695 20000 180001 resid[8,3] 0.1747 0.0724 2.822E-4 0.03371 0.1743 0.3189 20000 180001 resid[8,4] 0.04788 0.06665 4.225E-4 -0.08134 0.04756 0.1795 20000 180001 resid[8,5] -0.028 0.07432 5.503E-4 -0.1727 -0.02831 0.1181 20000 180001 resid[8,6] -0.02384 0.0727 5.281E-4 -0.1674 -0.02326 0.1171 20000 180001 resid[8,7] -0.0658 0.0675 4.634E-4 -0.1994 -0.06505 0.06478 20000 180001 resid[8,8] 0.0621 0.0653 4.429E-4 -0.06633 0.06255 0.1892 20000 180001 resid[8,9] -0.1023 0.06964 5.209E-4 -0.2385 -0.1024 0.03479 20000 180001 resid[8,10] 0.03976 0.1424 0.001366 -0.2361 0.03854 0.323 20000 180001 resid[9,1] 0.162 0.1307 8.189E-4 -0.07624 0.1564 0.4333 20000 180001 resid[9,2] 0.1897 0.0721 3.321E-4 0.05033 0.1886 0.335 20000 180001 resid[9,3] -0.05549 0.06979 3.81E-4 -0.1918 -0.05589 0.08204 20000 180001 resid[9,4] -0.1055 0.06944 4.039E-4 -0.2435 -0.105 0.02934 20000 180001 resid[9,5] -0.09182 0.06371 3.597E-4 -0.2185 -0.09133 0.03157 20000 180001 resid[9,6] 0.03423 0.05938 3.364E-4 -0.08342 0.0346 0.1492 20000 180001 resid[9,7] -0.07705 0.05685 3.548E-4 -0.1893 -0.07676 0.03334 20000 180001 resid[9,8] 0.02778 0.05819 4.051E-4 -0.08659 0.02783 0.1413 20000 180001 resid[9,9] -0.001504 0.06638 5.36E-4 -0.1312 -0.001275 0.1287 20000 180001 resid[9,10] 0.0315 0.146 0.001335 -0.2544 0.0305 0.3179 20000 180001 resid[10,1] -0.01471 0.1091 7.332E-4 -0.2354 -0.01237 0.1932 20000 180001 resid[10,2] -7.838E-4 0.09122 5.343E-4 -0.1817 8.053E-5 0.1764 20000 180001 resid[10,3] 0.01752 0.08215 4.301E-4 -0.1443 0.01788 0.1784 20000 180001 resid[10,4] -0.1173 0.06224 2.521E-4 -0.2395 -0.1172 0.005183 20000 180001 resid[10,5] 0.06291 0.06529 4.548E-4 -0.06383 0.06183 0.1934 20000 180001 resid[10,6] 0.003532 0.07278 5.721E-4 -0.1377 0.002814 0.1479 20000 180001 resid[10,7] -0.006866 0.07558 5.873E-4 -0.1569 -0.006438 0.1408 20000 180001 resid[10,8] 0.0432 0.07407 5.477E-4 -0.1044 0.04368 0.1872 20000 180001 resid[10,9] 0.01982 0.07469 5.733E-4 -0.1274 0.02003 0.1663 20000 180001 resid[10,10] 0.05437 0.1398 0.001575 -0.2168 0.05368 0.3309 20000 180001 resid[11,1] 0.03114 0.1386 8.277E-4 -0.2475 0.03274 0.2989 20000 180001 resid[11,2] 0.08273 0.08794 3.999E-4 -0.08452 0.08107 0.2612 20000 180001 resid[11,3] 0.04034 0.06898 3.67E-4 -0.09423 0.03989 0.1772 20000 180001 resid[11,4] -0.07807 0.07712 5.356E-4 -0.23 -0.07764 0.07376 20000 180001 resid[11,5] -0.07469 0.07219 5.021E-4 -0.2192 -0.07364 0.06501 20000 180001 resid[11,6] -0.05517 0.06685 4.581E-4 -0.1885 -0.05437 0.07441 20000 180001 resid[11,7] -0.02087 0.06231 4.275E-4 -0.1448 -0.02033 0.1002 20000 180001 resid[11,8] -0.03436 0.06223 4.428E-4 -0.158 -0.03387 0.08726 20000 180001 resid[11,9] -0.0332 0.07056 5.439E-4 -0.1724 -0.03266 0.1043 20000 180001 resid[11,10] -0.01977 0.1487 0.00126 -0.3113 -0.01972 0.2716 20000 180001 resid[12,1] -0.4525 0.1018 6.338E-4 -0.6565 -0.4505 -0.2579 20000 180001 resid[12,2] 0.1028 0.09266 5.308E-4 -0.0811 0.1039 0.2816 20000 180001 resid[12,3] 0.2753 0.07794 3.611E-4 0.1225 0.2755 0.4279 20000 180001 resid[12,4] 0.1489 0.06316 2.536E-4 0.02497 0.149 0.2727 20000 180001 resid[12,5] 0.06713 0.06516 4.527E-4 -0.05905 0.06663 0.1965 20000 180001 resid[12,6] 0.008456 0.07213 5.85E-4 -0.1306 0.007662 0.1519 20000 180001 resid[12,7] -0.0905 0.07525 6.197E-4 -0.2382 -0.09018 0.05633 20000 180001 resid[12,8] 0.0215 0.07437 5.83E-4 -0.1258 0.02242 0.1653 20000 180001 resid[12,9] 0.03574 0.07505 5.399E-4 -0.1129 0.03641 0.1829 20000 180001 resid[12,10] -0.08106 0.1535 0.001392 -0.3804 -0.08158 0.2242 20000 180001 sdD[1] 0.2224 0.05854 4.269E-4 0.137 0.2128 0.3626 20000 180001 sdD[2] 0.7196 0.1923 0.001033 0.4375 0.6886 1.181 20000 180001 sdD[3] 0.2959 0.07149 3.401E-4 0.1913 0.2843 0.468 20000 180001 sigma 0.173 0.01355 8.097E-5 0.1489 0.1721 0.2019 20000 180001 theta[1,1] -2.788 0.1343 0.001922 -3.073 -2.78 -2.544 20000 180001 theta[1,2] 0.3358 0.1937 0.001735 -0.03337 0.3321 0.7273 20000 180001 theta[1,3] -3.831 0.09507 0.001259 -4.033 -3.827 -3.658 20000 180001 theta[2,1] -2.298 0.08877 7.79E-4 -2.478 -2.296 -2.13 20000 180001 theta[2,2] 0.2841 0.1745 0.001375 -0.0506 0.2815 0.6339 20000 180001 theta[2,3] -3.116 0.0634 4.336E-4 -3.241 -3.115 -2.993 20000 180001 theta[3,1] -2.396 0.0916 8.189E-4 -2.585 -2.393 -2.226 20000 180001 theta[3,2] 0.7618 0.2262 0.00175 0.3472 0.7517 1.238 20000 180001 theta[3,3] -3.179 0.06504 5.003E-4 -3.309 -3.178 -3.053 20000 180001 theta[4,1] -2.388 0.09964 9.309E-4 -2.591 -2.385 -2.2 20000 180001 theta[4,2] -0.1178 0.1744 0.001425 -0.4547 -0.1201 0.2277 20000 180001 theta[4,3] -3.258 0.06795 5.455E-4 -3.394 -3.256 -3.129 20000 180001 theta[5,1] -2.434 0.1001 9.315E-4 -2.641 -2.431 -2.248 20000 180001 theta[5,2] 0.03741 0.1704 0.001417 -0.2887 0.03465 0.3791 20000 180001 theta[5,3] -3.151 0.06917 5.478E-4 -3.292 -3.15 -3.019 20000 180001 theta[6,1] -2.381 0.1 9.422E-4 -2.584 -2.378 -2.194 20000 180001 theta[6,2] -0.06325 0.1698 0.001418 -0.3921 -0.06468 0.2777 20000 180001 theta[6,3] -3.027 0.06725 5.208E-4 -3.162 -3.026 -2.899 20000 180001 theta[7,1] -2.364 0.113 0.001271 -2.595 -2.362 -2.15 20000 180001 theta[7,2] -0.5595 0.1647 0.001732 -0.8842 -0.5602 -0.2363 20000 180001 theta[7,3] -3.016 0.07014 5.758E-4 -3.159 -3.015 -2.882 20000 180001 theta[8,1] -2.474 0.1015 0.001018 -2.686 -2.47 -2.285 20000 180001 theta[8,2] 0.343 0.1881 0.001554 -0.01703 0.3383 0.7259 20000 180001 theta[8,3] -3.125 0.06997 5.689E-4 -3.266 -3.124 -2.991 20000 180001 theta[9,1] -2.488 0.09456 8.285E-4 -2.687 -2.485 -2.316 20000 180001 theta[9,2] 1.68 0.3855 0.00295 1.051 1.636 2.56 20000 180001 theta[9,3] -3.46 0.06944 5.867E-4 -3.599 -3.458 -3.327 20000 180001 theta[10,1] -2.577 0.1254 0.001516 -2.837 -2.572 -2.343 20000 180001 theta[10,2] -0.3108 0.1856 0.001837 -0.6708 -0.3122 0.06093 20000 180001 theta[10,3] -3.402 0.07987 7.95E-4 -3.566 -3.4 -3.253 20000 180001 theta[11,1] -2.342 0.08836 7.449E-4 -2.525 -2.339 -2.178 20000 180001 theta[11,2] 1.18 0.2671 0.002043 0.7085 1.163 1.759 20000 180001 theta[11,3] -2.91 0.06441 4.842E-4 -3.038 -2.908 -2.786 20000 180001 theta[12,1] -2.277 0.1026 0.001049 -2.484 -2.275 -2.083 20000 180001 theta[12,2] -0.3976 0.1644 0.001615 -0.7171 -0.3987 -0.0759 20000 180001 theta[12,3] -3.166 0.06531 4.665E-4 -3.296 -3.165 -3.039 20000 180001 node mean sd MC error 2.5% median 97.5% start sample list( N = 12, T = 10,Dose=c(4.02,4.4,4.53,4.4,5.86,4,4.95,4.53,3.1,5.5,4.92,5.3), Y = structure( .Data = c(2.84, 6.57, 10.50, 9.66, 8.58, 8.36, 7.47, 6.89, 5.94, 3.28, 1.72, 7.91, 8.31 ,8.33, 6.85, 6.08, 5.40, 4.55, 3.01, 0.90, 4.40, 6.90, 8.20, 7.80, 7.50, 6.20, 5.30, 4.90, 3.70, 1.05, 1.89, 4.60,8.60, 8.38, 7.54, 6.88, 5.78, 5.33, 4.19, 1.15, 2.02, 5.63, 11.40, 9.33, 8.74, 7.56, 7.09, 5.90, 4.37, 1.57, 1.29, 3.08, 6.44, 6.32, 5.53, 4.94, 4.02, 3.46, 2.78, 0.92, 0.85, 2.35, 5.02, 6.58, 7.09, 6.66, 5.25, 4.39, 3.53, 1.15, 3.05, 3.05, 7.31, 7.56, 6.59, 5.88,4.73, 4.57, 3.00, 1.25, 7.37, 9.03, 7.14 , 6.33 , 5.66 , 5.67, 4.24,4.11, 3.16, 1.12, 2.89 , 5.22, 6.41, 7.83 ,10.21, 9.18, 8.02, 7.14, 5.68, 2.42, 4.86, 7.24, 8.00, 6.81, 5.87, 5.22 , 4.45, 3.62 , 2.69, 0.86 , 1.25 , 3.96 , 7.82 , 9.72 , 9.75 , 8.57, 6.59, 6.11, 4.57 , 1.17), .Dim = c(12,10)), time = structure( .Data = c(0.25 , 0.57 , 1.12 , 2.02, 3.82 , 5.10 , 7.03 , 9.05, 12.12 ,24.37 , 0.27, 0.52, 1.00, 1.92, 3.50, 5.02, 7.03, 9.00, 12.00, 24.30, 0.27, 0.58 , 1.02, 2.02 , 3.62 , 5.08, 7.07, 9.00 ,12.15, 24.17 , 0.35 , 0.60 , 1.07 , 2.13 , 3.50 , 5.02 , 7.02 , 9.02 ,11.98 ,24.65 ,0.30 , 0.52 , 1.00, 2.02 , 3.50, 5.02, 7.02 , 9.10, 12.00 ,24.35, 0.27, 0.58, 1.15, 2.03, 3.57, 5.00 , 7.00, 9.22, 12.10 ,23.85 , 0.25, 0.50 , 1.02 , 2.02 , 3.48, 5.00, 6.98 , 9.00 ,12.05 ,24.22 , 0.25 , 0.52 , 0.98 , 2.02 , 3.53 , 5.05, 7.15, 9.07, 12.10 ,24.12 ,0.30 , 0.63 , 1.05 , 2.02 , 3.53 , 5.02 , 7.17 , 8.80 ,11.60 ,24.43 , 0.37 , 0.77 , 1.02 , 2.05 , 3.55 , 5.05 , 7.08 , 9.38 , 12.10, 23.70, 0.25 , 0.50 , 0.98 , 1.98 , 3.60 , 5.02, 7.03, 9.03 ,12.12 , 24.08 , 0.25 , 0.50 , 1.00 , 2.00, 3.52 , 5.07 , 7.07, 9.03, 12.05 ,24.15 ), .Dim = c(12,10)),mean = c(0, 0, 0),R = structure(.Data = c(0.2, 0, 0, 0, 0.2, 0, 0, 0, 0.2), .Dim = c(3, 3)), prec = structure(.Data = c(1.0E-6, 0, 0, 0, 1.0E-6, 0, 0, 0, 1.0E-6), .Dim = c(3, 3))) # Initial points list(theta = structure( .Data = c(-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3,-2.2,0,3), .Dim = c(12, 3)), beta = c(-2, .1, -3), Dinv = structure(.Data = c(1, 0, 0, 0, 1, 0, 0, 0, 1), .Dim = c(3, 3)), logtau = 0) PREVENT FLIP FLIP MODEL model { for( i in 1 : N ) { for( j in 1 : T ) { Y[i , j] ~ dlnorm(mu[i , j],eps.tau) mu[i , j] <- log(Dose[i]*exp(theta[i,1])*(exp(theta[i,1])+exp(theta[i,2]))*exp(- theta[i,3]) * (exp(-exp(theta[i,1])*time[i,j]) - exp(-(exp(theta[i,1])+exp(theta[i,2]))*time[i,j]) )/exp(theta[i,2])) fitted[i,j] <- mu[i,j] resid[i,j] <- log(Y[i,j])-fitted[i,j] } theta[i, 1:3] ~ dmnorm(beta[1:3], Dinv[1:3, 1:3]) ke[i] <- exp(theta[i,1]) ka[i] <- exp(theta[i,1])+exp(theta[i,2]) Cl[i] <- exp(theta[i,3]) } eps.tau <- exp(logtau) logtau ~ dflat() sigma <- 1 / sqrt(eps.tau) beta[1:3] ~ dmnorm(mean[1:3], prec[1:3, 1:3]) kemean <- exp(beta[1]+sqrt(sdD[1,1])) kamean <- exp(beta[1]+sqrt(sdD[1,1]))+exp(beta[2]+sqrt(sdD[2,2])) Clmean <- exp(beta[3]+sqrt(sdD[2,2])) kemed <- exp(beta[1]) Clmed <- exp(beta[3]) Dinv[1:3, 1:3] ~ dwish(R[1:3, 1:3], 3) D[1:3, 1:3] <- inverse(Dinv[1:3, 1:3]) for (i in 1 : 3) {sdD[i] <- sqrt(D[i, i]) } }