Dati(1,1).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 96.875% 87.5% fit rms cod fit rms cod 1 0.89234 0.085576 0.98841 0.90498 0.075534 0.99097 2 0.88308 0.092941 0.98633 0.84098 0.12641 0.97471 3 0.85585 0.11458 0.97922 0.78656 0.16967 0.95444 4 0.84008 0.12712 0.97442 0.75387 0.19565 0.93942 5 0.80738 0.15312 0.9629 0.72024 0.22238 0.92173 6 0.798 0.16057 0.9592 0.67951 0.25476 0.89728 7 0.77792 0.17653 0.95068 0.64955 0.27857 0.87719 8 0.77662 0.17756 0.9501 0.62652 0.29688 0.86051 9 0.73929 0.20724 0.93203 0.60256 0.31593 0.84204 10 0.73834 0.20799 0.93154 0.57198 0.34023 0.8168 11 0.6982 0.2399 0.90892 0.55078 0.35708 0.79821 12 0.71346 0.22777 0.91789 0.52888 0.3745 0.77804 13 0.67877 0.25534 0.89681 0.49998 0.39746 0.74998 14 0.69627 0.24144 0.90775 0.46509 0.4252 0.71387 15 0.66946 0.26275 0.89074 0.42933 0.45363 0.67434 16 0.68824 0.24782 0.9028 0.40102 0.47613 0.64122 17 0.62932 0.29465 0.8626 0.36973 0.501 0.60276 18 0.65968 0.27052 0.88418 0.33739 0.52671 0.56095 19 0.61355 0.30719 0.85066 0.30501 0.55245 0.51699 20 0.63614 0.28924 0.8676 0.27721 0.57455 0.47757 21 0.57052 0.34139 0.81555 0.24843 0.59742 0.43515 22 0.59853 0.31913 0.83882 0.21894 0.62087 0.38994 23 0.54344 0.36292 0.79156 0.18955 0.64423 0.34317 24 0.54372 0.3627 0.79181 0.16218 0.66598 0.29806 25 0.43841 0.44641 0.68462 0.13459 0.68791 0.25107 26 0.44811 0.4387 0.69541 0.10481 0.71159 0.19863 27 0.34211 0.52296 0.56718 0.074469 0.73571 0.14339 28 0.31993 0.54059 0.53751 0.045289 0.7589 0.088526 29 0.17939 0.6523 0.3266 0.016033 0.78216 0.031809 30 0.14462 0.67994 0.26833 -0.014131 0.80613 -0.028462 Dati(1,2).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 93.75% fit rms cod fit rms cod 1 -0.12179 1.3401 -0.25842 0.18729 0.97084 0.3395 2 -0.48459 1.7734 -1.204 0.1657 0.99663 0.30394 3 -1.0819 2.487 -3.3344 0.14547 1.0208 0.26978 4 -0.84427 2.2031 -2.4013 0.12181 1.0491 0.22879 5 -0.24393 1.486 -0.54737 0.082026 1.0966 0.15732 6 0.17619 0.9841 0.32134 0.071175 1.1095 0.13728 7 0.47219 0.63051 0.72142 0.064931 1.117 0.12565 8 0.20722 0.94703 0.3715 0.056851 1.1267 0.11047 9 -0.23923 1.4803 -0.53569 0.033259 1.1548 0.065412 10 -0.39591 1.6675 -0.94855 0.030658 1.1579 0.060375 11 -0.53544 1.8342 -1.3576 0.028629 1.1604 0.056438 12 0.04361 1.1425 0.085317 0.026597 1.1628 0.052487 13 0.21262 0.94058 0.38004 0.02425 1.1656 0.047912 14 0.28528 0.85379 0.48917 0.023438 1.1666 0.046326 15 0.1807 0.97872 0.32874 0.022914 1.1672 0.045304 16 -0.29355 1.5452 -0.67326 0.022378 1.1678 0.044256 17 -0.43207 1.7107 -1.0508 0.021648 1.1687 0.042827 18 -0.46761 1.7532 -1.1539 0.02147 1.1689 0.042479 19 -0.1079 1.3235 -0.22745 0.02134 1.1691 0.042225 20 0.127 1.0429 0.23788 0.021226 1.1692 0.042002 21 0.12501 1.0452 0.2344 0.021123 1.1693 0.041799 22 0.11126 1.0617 0.21014 0.021079 1.1694 0.041713 23 -0.19483 1.4273 -0.42761 0.021049 1.1694 0.041655 24 -0.39558 1.6671 -0.94765 0.021023 1.1695 0.041604 25 -0.31656 1.5727 -0.73332 0.020999 1.1695 0.041557 26 -0.12807 1.3476 -0.27254 0.02099 1.1695 0.041539 27 0.026344 1.1631 0.051993 0.020983 1.1695 0.041526 28 0.023663 1.1663 0.046766 0.020978 1.1695 0.041516 29 0.027902 1.1612 0.055025 0.020974 1.1695 0.041508 30 -0.10052 1.3147 -0.21115 0.020972 1.1695 0.041504 Dati(1,3).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 71.875% 78.125% fit rms cod fit rms cod 1 0.92124 0.12112 0.9938 0.27982 1.1075 0.48133 2 0.90765 0.14203 0.99147 0.19811 1.2332 0.35697 3 0.90275 0.14956 0.99054 0.18516 1.2531 0.33604 4 0.90131 0.15176 0.99026 0.19431 1.239 0.35087 5 0.9003 0.15333 0.99006 0.12534 1.3451 0.23497 6 0.90006 0.15369 0.99001 0.20359 1.2247 0.36574 7 0.89998 0.15381 0.99 0.22112 1.1978 0.39335 8 0.89996 0.15384 0.98999 0.22695 1.1888 0.4024 9 0.89995 0.15386 0.98999 0.21904 1.201 0.3901 10 0.89995 0.15387 0.98999 0.23338 1.1789 0.4123 11 0.89995 0.15387 0.98999 0.22719 1.1885 0.40276 12 0.89995 0.15387 0.98999 0.22514 1.1916 0.3996 13 0.89995 0.15387 0.98999 0.2233 1.1944 0.39673 14 0.89995 0.15387 0.98999 0.22535 1.1913 0.39992 15 0.89995 0.15387 0.98999 0.22342 1.1942 0.39693 16 0.89994 0.15387 0.98999 0.22376 1.1937 0.39746 17 0.89994 0.15387 0.98999 0.22383 1.1936 0.39757 18 0.89994 0.15387 0.98999 0.22425 1.193 0.39821 19 0.89994 0.15387 0.98999 0.2239 1.1935 0.39767 20 0.89994 0.15387 0.98999 0.2241 1.1932 0.39798 21 0.89994 0.15387 0.98999 0.22408 1.1932 0.39796 22 0.89994 0.15387 0.98999 0.22411 1.1932 0.398 23 0.89994 0.15387 0.98999 0.22405 1.1933 0.39789 24 0.89994 0.15387 0.98999 0.22409 1.1932 0.39796 25 0.89994 0.15387 0.98999 0.22407 1.1932 0.39794 26 0.89994 0.15387 0.98999 0.22407 1.1932 0.39794 27 0.89994 0.15387 0.98999 0.22407 1.1933 0.39793 28 0.89994 0.15387 0.98999 0.22408 1.1932 0.39794 29 0.89994 0.15387 0.98999 0.22407 1.1932 0.39793 30 0.89994 0.15387 0.98999 0.22407 1.1932 0.39794 Dati(1,4).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 78.125% fit rms cod fit rms cod 1 -0.60196 2.2782 -1.5663 0.78146 0.31079 0.95224 2 -1.4472 3.4802 -4.9888 0.73754 0.37326 0.93111 3 -1.138 3.0404 -3.5709 0.71523 0.40498 0.91891 4 -0.31863 1.8752 -0.73877 0.6984 0.42891 0.90904 5 0.26686 1.0426 0.4625 0.65141 0.49574 0.87848 6 0.07269 1.3187 0.1401 0.64658 0.50261 0.87509 7 0.25271 1.0627 0.44156 0.6408 0.51083 0.87097 8 0.44865 0.78408 0.69602 0.63556 0.51828 0.86718 9 -0.033048 1.4691 -0.067188 0.62608 0.53176 0.86018 10 0.47002 0.7537 0.71912 0.62609 0.53175 0.86019 11 -0.67142 2.377 -1.7936 0.62454 0.53395 0.85903 12 -1.6101 3.7119 -5.8126 0.62325 0.53578 0.85806 13 -1.3636 3.3614 -4.5868 0.62152 0.53824 0.85675 14 -0.1907 1.6933 -0.41777 0.62168 0.53801 0.85688 15 -0.094708 1.5568 -0.19839 0.62128 0.53859 0.85657 16 -0.39866 1.9891 -0.95625 0.621 0.53898 0.85636 17 -0.20769 1.7175 -0.45852 0.62071 0.5394 0.85614 18 -0.22413 1.7409 -0.49848 0.62076 0.53933 0.85618 19 -1.3186 3.2973 -4.3758 0.62066 0.53947 0.8561 20 -0.27688 1.8159 -0.63041 0.62061 0.53954 0.85606 21 -0.59787 2.2724 -1.5532 0.62056 0.53961 0.85602 22 -1.9379 4.178 -7.6311 0.62057 0.5396 0.85603 23 -0.95832 2.785 -2.835 0.62055 0.53963 0.85602 24 -0.065167 1.5148 -0.13458 0.62054 0.53964 0.85601 25 -0.30998 1.863 -0.71605 0.62053 0.53965 0.856 26 -1.1775 3.0967 -3.7417 0.62053 0.53965 0.85601 27 -0.72748 2.4567 -1.9842 0.62053 0.53965 0.856 28 -1.1748 3.0929 -3.7299 0.62053 0.53966 0.856 29 -2.8297 5.4463 -13.6666 0.62053 0.53966 0.856 30 -1.1972 3.1247 -3.8279 0.62053 0.53966 0.856 Dati(1,5).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 96.875% fit rms cod fit rms cod 1 0.59073 0.51689 0.8325 0.23651 0.96426 0.41709 2 0.37979 0.7833 0.61535 0.21597 0.99021 0.3853 3 0.34318 0.82954 0.56859 0.19612 1.0153 0.35377 4 0.2634 0.93031 0.45742 0.18499 1.0293 0.33576 5 0.010018 1.2503 0.019936 0.12734 1.1021 0.23847 6 -0.079026 1.3628 -0.1643 0.1165 1.1158 0.21943 7 0.022232 1.2349 0.043971 0.10883 1.1255 0.20582 8 0.00045526 1.2624 0.00091032 0.11322 1.12 0.21362 9 -0.21616 1.536 -0.47905 0.073561 1.1701 0.14171 10 -0.13308 1.431 -0.28388 0.081558 1.16 0.15646 11 0.0031494 1.259 0.0062888 0.093281 1.1452 0.17786 12 -0.061661 1.3408 -0.12712 0.094107 1.1441 0.17936 13 -0.20941 1.5274 -0.46266 0.089853 1.1495 0.17163 14 -0.075255 1.358 -0.15617 0.090708 1.1484 0.17319 15 0.048701 1.2015 0.095031 0.092071 1.1467 0.17567 16 -0.073607 1.3559 -0.15263 0.093043 1.1455 0.17743 17 -0.17763 1.4873 -0.3868 0.091285 1.1477 0.17424 18 0.0033666 1.2587 0.0067219 0.091964 1.1468 0.17547 19 0.052277 1.1969 0.10182 0.093 1.1455 0.17735 20 -0.099137 1.3882 -0.2081 0.0929 1.1456 0.17717 21 -0.13647 1.4353 -0.29156 0.092473 1.1462 0.17639 22 0.037772 1.2153 0.074118 0.092567 1.1461 0.17657 23 0.030486 1.2245 0.060042 0.092719 1.1459 0.17684 24 -0.1343 1.4326 -0.28665 0.092745 1.1458 0.17689 25 -0.095367 1.3834 -0.19983 0.092627 1.146 0.17668 26 0.044904 1.2063 0.087792 0.092652 1.146 0.17672 27 -0.0091238 1.2745 -0.018331 0.092713 1.1459 0.17683 28 -0.15585 1.4598 -0.33598 0.092696 1.1459 0.1768 29 -0.053331 1.3303 -0.10951 0.092663 1.1459 0.17674 30 0.030221 1.2248 0.059529 0.092671 1.1459 0.17675 Dati(1,6).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 93.75% fit rms cod fit rms cod 1 0.6925 0.40503 0.90545 0.28407 0.94301 0.48744 2 0.51532 0.6384 0.76509 0.21262 1.0371 0.38004 3 0.38862 0.80529 0.62622 0.16403 1.1011 0.30115 4 0.30331 0.91766 0.51462 0.11667 1.1635 0.21973 5 0.073349 1.2206 0.14132 0.040894 1.2633 0.080115 6 -0.18765 1.5643 -0.41052 0.014289 1.2984 0.028374 7 -0.41733 1.8669 -1.0088 -0.00028426 1.3175 -0.00056861 8 -0.67557 2.207 -1.8075 -0.011952 1.3329 -0.024046 9 -0.94869 2.5668 -2.7974 -0.022486 1.3468 -0.045478 10 -1.2634 2.9813 -4.1231 -0.028028 1.3541 -0.056841 11 -1.7395 3.6084 -6.5051 -0.0313 1.3584 -0.063581 12 -2.3336 4.3909 -10.1128 -0.033624 1.3615 -0.068379 13 -2.9766 5.2378 -14.8131 -0.035333 1.3637 -0.071914 14 -3.5241 5.959 -19.4674 -0.036368 1.3651 -0.074059 15 -4.2259 6.8835 -26.3105 -0.037011 1.3659 -0.075392 16 -5.083 8.0123 -36.0027 -0.037443 1.3665 -0.076288 17 -6.0733 9.3168 -49.0319 -0.037736 1.3669 -0.076896 18 -7.0078 10.5476 -63.1246 -0.037922 1.3671 -0.077281 19 -8.0793 11.959 -81.4335 -0.038039 1.3673 -0.077525 20 -9.3442 13.625 -106.0015 -0.038116 1.3674 -0.077685 21 -10.7854 15.5235 -137.8967 -0.038166 1.3674 -0.07779 22 -12.4277 17.6866 -179.3018 -0.038199 1.3675 -0.077857 23 -14.2702 20.1136 -232.1803 -0.038219 1.3675 -0.077899 24 -16.316 22.8081 -298.8422 -0.038233 1.3675 -0.077927 25 -18.5707 25.778 -382.0104 -0.038241 1.3675 -0.077945 26 -21.0767 29.0789 -486.382 -0.038247 1.3676 -0.077956 27 -23.9603 32.8771 -622.0181 -0.03825 1.3676 -0.077963 28 -27.0612 36.9615 -786.4332 -0.038252 1.3676 -0.077968 29 -30.4812 41.4663 -990.068 -0.038254 1.3676 -0.077971 30 -34.262 46.4462 -1242.407 -0.038255 1.3676 -0.077973 Dati(1,7).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 90.625% 96.875% fit rms cod fit rms cod 1 0.91068 0.098828 0.99202 0.20791 0.87643 0.37259 2 0.78935 0.23309 0.95562 0.13486 0.95726 0.25154 3 0.66245 0.37349 0.88606 0.083375 1.0142 0.1598 4 0.55421 0.49326 0.80127 0.045757 1.0559 0.08942 5 0.4785 0.57703 0.72804 -0.00056898 1.1071 -0.0011383 6 0.44431 0.61486 0.69121 0.0021746 1.1041 0.0043445 7 0.45137 0.60705 0.699 -0.0025867 1.1093 -0.0051801 8 0.49188 0.56223 0.74181 -0.0053339 1.1124 -0.010696 9 0.55297 0.49463 0.80017 -0.0072048 1.1145 -0.014461 10 0.62011 0.42034 0.85568 -0.0067589 1.114 -0.013563 11 0.67918 0.35498 0.89708 -0.0071795 1.1144 -0.014411 12 0.72038 0.30939 0.92181 -0.0072993 1.1146 -0.014652 13 0.74087 0.28672 0.93285 -0.0073539 1.1146 -0.014762 14 0.74244 0.28499 0.93366 -0.0073286 1.1146 -0.014711 15 0.72836 0.30057 0.92621 -0.0073593 1.1146 -0.014773 16 0.70248 0.3292 0.91148 -0.0073608 1.1146 -0.014776 17 0.66998 0.36517 0.89108 -0.0073621 1.1146 -0.014778 18 0.63745 0.40115 0.86856 -0.0073614 1.1146 -0.014777 19 0.61099 0.43044 0.84867 -0.0073632 1.1146 -0.014781 20 0.59496 0.44817 0.83594 -0.0073629 1.1146 -0.01478 21 0.59079 0.45278 0.83255 -0.007363 1.1146 -0.01478 22 0.59739 0.44549 0.8379 -0.007363 1.1146 -0.01478 23 0.61156 0.4298 0.84911 -0.0073631 1.1146 -0.01478 24 0.62912 0.41037 0.86245 -0.007363 1.1146 -0.01478 25 0.64621 0.39147 0.87483 -0.007363 1.1146 -0.01478 26 0.65977 0.37646 0.88425 -0.007363 1.1146 -0.01478 27 0.66822 0.3671 0.88992 -0.007363 1.1146 -0.01478 28 0.67133 0.36367 0.89198 -0.007363 1.1146 -0.01478 29 0.66969 0.36548 0.8909 -0.007363 1.1146 -0.01478 30 0.66432 0.37142 0.88732 -0.007363 1.1146 -0.01478 Dati(1,8).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 71.875% fit rms cod fit rms cod 1 0.33642 0.91032 0.55966 0.91018 0.12321 0.99193 2 0.22199 1.0673 0.3947 0.8987 0.13897 0.98974 3 0.17469 1.1322 0.31886 0.89415 0.14521 0.9888 4 0.090535 1.2476 0.17287 0.89049 0.15023 0.98801 5 0.18525 1.1177 0.33619 0.87812 0.16719 0.98515 6 0.42148 0.79364 0.66531 0.87959 0.16518 0.9855 7 0.28963 0.97451 0.49537 0.87936 0.1655 0.98545 8 0.32623 0.9243 0.54603 0.87866 0.16646 0.98528 9 0.041023 1.3156 0.080363 0.87689 0.16889 0.98484 10 -0.099887 1.5089 -0.20975 0.87777 0.16767 0.98506 11 -0.15537 1.585 -0.33489 0.87768 0.1678 0.98504 12 -0.067886 1.465 -0.14038 0.87755 0.16798 0.98501 13 -0.029189 1.4119 -0.059229 0.87734 0.16826 0.98496 14 0.19335 1.1066 0.34932 0.87756 0.16797 0.98501 15 0.13271 1.1898 0.2478 0.8775 0.16804 0.98499 16 0.13632 1.1848 0.25406 0.87749 0.16807 0.98499 17 -0.016496 1.3945 -0.033264 0.87747 0.16809 0.98499 18 -0.096401 1.5041 -0.2021 0.87751 0.16804 0.985 19 -0.1875 1.629 -0.41016 0.87749 0.16806 0.98499 20 -0.05935 1.4532 -0.12222 0.87749 0.16807 0.98499 21 -0.043895 1.432 -0.089716 0.87749 0.16807 0.98499 22 0.08959 1.2489 0.17115 0.87749 0.16806 0.98499 23 0.069822 1.276 0.13477 0.87749 0.16806 0.98499 24 0.0701 1.2757 0.13529 0.87749 0.16806 0.98499 25 -0.02948 1.4123 -0.059829 0.87749 0.16806 0.98499 26 -0.056096 1.4488 -0.11534 0.87749 0.16806 0.98499 27 -0.14653 1.5729 -0.31454 0.87749 0.16806 0.98499 28 -0.042156 1.4297 -0.08609 0.87749 0.16806 0.98499 29 -0.031874 1.4156 -0.064764 0.87749 0.16806 0.98499 30 0.032564 1.3272 0.064068 0.87749 0.16806 0.98499 Dati(1,9).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 68.75% 0% fit rms cod fit rms cod 1 0.45642 2.6088 0.70453 0.66708 1.5978 0.88916 2 0.31228 3.3005 0.52704 0.40055 2.8769 0.64066 3 0.27411 3.4837 0.47308 0.1736 3.9661 0.31706 4 0.264 3.5322 0.45831 -0.073772 5.1533 -0.15299 5 0.26132 3.5451 0.45435 -0.23431 5.9237 -0.52351 6 0.26061 3.5485 0.4533 -0.28873 6.1849 -0.66081 7 0.26042 3.5494 0.45303 -0.26554 6.0737 -0.6016 8 0.26037 3.5496 0.45295 -0.22442 5.8763 -0.49921 9 0.26036 3.5497 0.45293 -0.16524 5.5922 -0.35777 10 0.26036 3.5497 0.45293 -0.097456 5.267 -0.20441 11 0.26036 3.5497 0.45293 -0.045847 5.0193 -0.093796 12 0.26036 3.5497 0.45293 -0.011089 4.8525 -0.022301 13 0.26036 3.5497 0.45293 0.020154 4.7025 0.039902 14 0.26036 3.5497 0.45293 0.046372 4.5767 0.090594 15 0.26036 3.5497 0.45293 0.057294 4.5243 0.1113 16 0.26036 3.5497 0.45293 0.063674 4.4937 0.12329 17 0.26036 3.5497 0.45293 0.051472 4.5522 0.10029 18 0.26036 3.5497 0.45293 0.020274 4.7019 0.040136 19 0.26036 3.5497 0.45293 -0.010586 4.85 -0.021284 20 0.26036 3.5497 0.45293 -0.050191 5.0401 -0.1029 21 0.26036 3.5497 0.45293 -0.098225 5.2706 -0.2061 22 0.26036 3.5497 0.45293 -0.11035 5.3288 -0.23287 23 0.26036 3.5497 0.45293 -0.10933 5.3239 -0.23062 24 0.26036 3.5497 0.45293 -0.090888 5.2354 -0.19004 25 0.26036 3.5497 0.45293 -0.063505 5.104 -0.13104 26 0.26036 3.5497 0.45293 -0.059348 5.0841 -0.12222 27 0.26036 3.5497 0.45293 -0.079222 5.1794 -0.16472 28 0.26036 3.5497 0.45293 -0.10999 5.3271 -0.23208 29 0.26036 3.5497 0.45293 -0.12248 5.3871 -0.25997 30 0.26036 3.5497 0.45293 -0.098776 5.2733 -0.20731 Dati(1,10).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 87.5% fit rms cod fit rms cod 1 0.39218 0.91626 0.63055 0.53997 0.69348 0.78837 2 0.28533 1.0773 0.48925 0.4254 0.86619 0.66983 3 0.27276 1.0963 0.47112 0.35185 0.97705 0.57991 4 0.57611 0.63899 0.82032 0.29419 1.064 0.50183 5 0.68505 0.47477 0.90081 0.21376 1.1852 0.38183 6 0.69072 0.46623 0.90434 0.22013 1.1756 0.39181 7 0.48377 0.77819 0.73351 0.21448 1.1841 0.38295 8 -0.0049106 1.5149 -0.0098453 0.2103 1.1904 0.37638 9 -0.46906 2.2145 -1.1581 0.20639 1.1963 0.37019 10 -0.47879 2.2292 -1.1868 0.21356 1.1855 0.38151 11 -0.036336 1.5622 -0.073993 0.21347 1.1857 0.38137 12 0.32995 1.0101 0.55103 0.21402 1.1848 0.38223 13 0.3297 1.0104 0.5507 0.21455 1.184 0.38307 14 0.33094 1.0086 0.55236 0.21583 1.1821 0.38507 15 0.19397 1.2151 0.35032 0.21553 1.1826 0.38461 16 -0.43495 2.1631 -1.0591 0.21567 1.1823 0.38483 17 -1.0798 3.1353 -3.3258 0.21575 1.1822 0.38495 18 -0.49485 2.2534 -1.2346 0.21584 1.1821 0.38509 19 0.037625 1.4507 0.073835 0.21573 1.1822 0.38493 20 -0.44123 2.1726 -1.0771 0.21576 1.1822 0.38497 21 -0.50016 2.2614 -1.2505 0.21576 1.1822 0.38496 22 -0.10721 1.6691 -0.22591 0.21576 1.1822 0.38496 23 -0.19118 1.7956 -0.4189 0.21574 1.1822 0.38493 24 -1.233 3.3661 -3.9861 0.21575 1.1822 0.38494 25 -1.8041 4.2271 -6.863 0.21574 1.1822 0.38494 26 -0.59953 2.4112 -1.5585 0.21574 1.1822 0.38494 27 -0.45471 2.1929 -1.1162 0.21574 1.1822 0.38494 28 -1.8114 4.238 -6.9039 0.21574 1.1822 0.38494 29 -1.5349 3.8213 -5.4259 0.21574 1.1822 0.38494 30 -0.22435 1.8457 -0.49903 0.21574 1.1822 0.38494 Dati(1,11).t.glar.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 0% fit rms cod fit rms cod 1 0.53455 0.3705 0.78335 0.67259 0.26062 0.8928 2 0.017089 0.78239 0.033887 0.57505 0.33826 0.81942 3 -0.24541 0.99134 -0.55105 0.36747 0.50349 0.5999 4 -0.48194 1.1796 -1.1961 0.25205 0.59536 0.44057 5 -0.68976 1.345 -1.8553 0.09503 0.72035 0.18103 6 -0.67466 1.333 -1.8045 0.13472 0.68876 0.25129 7 -0.57264 1.2518 -1.4732 0.056758 0.75081 0.1103 8 -0.49996 1.194 -1.2499 0.10691 0.71089 0.20239 9 -0.47654 1.1753 -1.1802 0.033407 0.7694 0.065697 10 -0.44298 1.1486 -1.0822 0.10493 0.71247 0.19885 11 -0.36793 1.0889 -0.87123 -0.0064108 0.8011 -0.012863 12 -0.2789 1.018 -0.63559 0.083738 0.72934 0.16046 13 -0.23803 0.98546 -0.53272 -2.925e-06 0.796 -5.8501e-06 14 -0.1989 0.95432 -0.43737 0.12354 0.69766 0.23182 15 -0.07851 0.85849 -0.16318 0.045238 0.75998 0.08843 16 0.036602 0.76686 0.071864 0.1563 0.67158 0.28818 17 0.068555 0.74142 0.13241 0.047058 0.75854 0.091902 18 0.068708 0.7413 0.1327 0.14808 0.67812 0.27424 19 0.069409 0.74074 0.134 0.02326 0.77748 0.045978 20 0.0073669 0.79013 0.014679 0.14692 0.67905 0.27225 21 -0.096571 0.87286 -0.20247 0.0084756 0.78925 0.016879 22 -0.18253 0.94129 -0.39839 0.1166 0.70318 0.2196 23 -0.2676 1.009 -0.60682 -0.055239 0.83996 -0.11353 24 -0.33393 1.0618 -0.77936 0.076459 0.73513 0.14707 25 -0.35974 1.0823 -0.84889 -0.16487 0.92723 -0.35693 26 -0.36151 1.0838 -0.85371 -0.0040409 0.79921 -0.0080982 27 -0.33164 1.06 -0.77327 -0.27092 1.0116 -0.61523 28 -0.28252 1.0209 -0.64485 -0.068514 0.85053 -0.14172 29 -0.24504 0.99104 -0.55012 -0.38443 1.102 -0.91664 30 -0.20277 0.9574 -0.44666 -0.12519 0.89565 -0.26606