Dati(1,1).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 96.875% 75% fit rms cod fit rms cod 1 0.85867 0.096849 0.98003 0.94601 0.036995 0.99709 2 0.81247 0.12851 0.96483 0.90731 0.063518 0.99141 3 0.76355 0.16204 0.94409 0.8784 0.083333 0.98521 4 0.72031 0.19166 0.92178 0.85786 0.097403 0.9798 5 0.65261 0.23806 0.87932 0.83883 0.11045 0.97402 6 0.62162 0.2593 0.85683 0.82032 0.12313 0.96772 7 0.58056 0.28743 0.82407 0.80683 0.13237 0.96269 8 0.58168 0.28667 0.82501 0.79786 0.13852 0.95914 9 0.51977 0.32909 0.76938 0.78638 0.14639 0.95437 10 0.49741 0.34441 0.74741 0.77392 0.15493 0.94889 11 0.44643 0.37935 0.69356 0.76336 0.16216 0.944 12 0.45688 0.37219 0.70502 0.75335 0.16902 0.93917 13 0.42966 0.39084 0.67471 0.7418 0.17694 0.93333 14 0.44776 0.37844 0.69503 0.72872 0.18591 0.92641 15 0.4275 0.39232 0.67225 0.71667 0.19416 0.91972 16 0.46331 0.36778 0.71197 0.70586 0.20157 0.91348 17 0.38626 0.42058 0.62332 0.69438 0.20943 0.9066 18 0.42916 0.39119 0.67414 0.6821 0.21785 0.89894 19 0.38678 0.42023 0.62396 0.67042 0.22586 0.89137 20 0.42081 0.3969 0.66454 0.65962 0.23325 0.88414 21 0.35389 0.44276 0.58255 0.64894 0.24057 0.87676 22 0.42144 0.39647 0.66527 0.63792 0.24813 0.8689 23 0.37891 0.42562 0.61424 0.62712 0.25553 0.86096 24 0.44845 0.37797 0.69579 0.6169 0.26253 0.85323 25 0.33021 0.45899 0.55139 0.60648 0.26967 0.84515 26 0.41068 0.40385 0.65271 0.59565 0.27709 0.8365 27 0.31579 0.46888 0.53185 0.58486 0.28449 0.82766 28 0.41041 0.40404 0.65238 0.57421 0.29178 0.81871 29 0.28389 0.49074 0.48719 0.56347 0.29915 0.80944 30 0.39901 0.41185 0.63881 0.55251 0.30666 0.79975 Dati(1,2).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 84.375% 50% fit rms cod fit rms cod 1 0.94231 0.044251 0.99667 0.93587 0.04919 0.99589 2 0.90134 0.075674 0.99027 0.91965 0.061625 0.99354 3 0.85787 0.10901 0.9798 0.91701 0.063654 0.99311 4 0.84548 0.11852 0.97612 0.91245 0.067153 0.99233 5 0.85948 0.10778 0.98025 0.88702 0.086658 0.98723 6 0.88131 0.091035 0.98591 0.87098 0.098955 0.98335 7 0.90639 0.071802 0.99124 0.86009 0.10731 0.98043 8 0.91571 0.064647 0.9929 0.86281 0.10523 0.98118 9 0.91757 0.063222 0.99321 0.84438 0.11936 0.97578 10 0.91711 0.063574 0.99313 0.82616 0.13333 0.96978 11 0.91775 0.063086 0.99323 0.8141 0.14258 0.96544 12 0.91619 0.064284 0.99298 0.81492 0.14196 0.96574 13 0.90063 0.076214 0.99013 0.80261 0.1514 0.96104 14 0.86822 0.10108 0.98263 0.78871 0.16206 0.95536 15 0.83771 0.12448 0.97366 0.77395 0.17338 0.9489 16 0.82285 0.13587 0.96862 0.77262 0.1744 0.9483 17 0.839 0.12348 0.97408 0.76513 0.18014 0.94484 18 0.86965 0.099982 0.98301 0.75427 0.18847 0.93962 19 0.89377 0.081481 0.98871 0.73995 0.19946 0.93238 20 0.89517 0.080405 0.98901 0.73643 0.20216 0.93053 21 0.88754 0.08626 0.98735 0.73095 0.20636 0.92761 22 0.88575 0.087628 0.98695 0.72368 0.21194 0.92364 23 0.89348 0.081704 0.98865 0.71119 0.22152 0.91659 24 0.899 0.077468 0.9898 0.70579 0.22566 0.91344 25 0.88406 0.088928 0.98656 0.7011 0.22926 0.91066 26 0.85003 0.11503 0.97751 0.69625 0.23298 0.90773 27 0.82077 0.13747 0.96788 0.68601 0.24083 0.90141 28 0.81325 0.14324 0.96512 0.67992 0.2455 0.89755 29 0.83311 0.12801 0.97215 0.67523 0.2491 0.89452 30 0.86491 0.10362 0.98175 0.67192 0.25163 0.89237 Dati(1,3).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 71.875% 65.625% fit rms cod fit rms cod 1 0.8992 0.085851 0.98984 0.94187 0.049508 0.99662 2 0.90592 0.080132 0.99115 0.91031 0.076392 0.99196 3 0.90521 0.080736 0.99101 0.89012 0.09359 0.98793 4 0.90527 0.08068 0.99103 0.87941 0.10271 0.98546 5 0.90526 0.080689 0.99103 0.86893 0.11163 0.98282 6 0.90527 0.080688 0.99103 0.8641 0.11575 0.98153 7 0.90527 0.080688 0.99103 0.86516 0.11485 0.98182 8 0.90527 0.080688 0.99103 0.87122 0.10968 0.98342 9 0.90527 0.080688 0.99103 0.87716 0.10463 0.98491 10 0.90527 0.080688 0.99103 0.88282 0.099807 0.98627 11 0.90527 0.080688 0.99103 0.88763 0.095712 0.98737 12 0.90527 0.080688 0.99103 0.89102 0.09282 0.98812 13 0.90527 0.080688 0.99103 0.89267 0.091414 0.98848 14 0.90527 0.080688 0.99103 0.89319 0.090971 0.98859 15 0.90527 0.080688 0.99103 0.89289 0.09123 0.98853 16 0.90527 0.080688 0.99103 0.89201 0.091976 0.98834 17 0.90527 0.080688 0.99103 0.89058 0.093197 0.98803 18 0.90527 0.080688 0.99103 0.88876 0.094749 0.98762 19 0.90527 0.080688 0.99103 0.88705 0.096199 0.98724 20 0.90527 0.080688 0.99103 0.88593 0.097158 0.98699 21 0.90527 0.080688 0.99103 0.88526 0.09773 0.98683 22 0.90527 0.080688 0.99103 0.88499 0.097953 0.98677 23 0.90527 0.080688 0.99103 0.88511 0.097857 0.9868 24 0.90527 0.080688 0.99103 0.88553 0.097497 0.9869 25 0.90527 0.080688 0.99103 0.88612 0.096999 0.98703 26 0.90527 0.080688 0.99103 0.88669 0.096505 0.98716 27 0.90527 0.080688 0.99103 0.88719 0.09608 0.98727 28 0.90527 0.080688 0.99103 0.88757 0.095758 0.98736 29 0.90527 0.080688 0.99103 0.88781 0.095558 0.98741 30 0.90527 0.080688 0.99103 0.88789 0.095486 0.98743 Dati(1,4).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 87.5% 75% fit rms cod fit rms cod 1 0.88613 0.090905 0.98703 0.95465 0.036208 0.99794 2 0.81084 0.15101 0.96422 0.91069 0.071297 0.99202 3 0.79383 0.16459 0.9575 0.86622 0.1068 0.9821 4 0.79798 0.16128 0.95919 0.82147 0.14253 0.96813 5 0.79991 0.15974 0.95996 0.7788 0.17659 0.95107 6 0.78488 0.17174 0.95372 0.73436 0.21208 0.92943 7 0.78678 0.17022 0.95454 0.68692 0.24994 0.90198 8 0.80758 0.15362 0.96297 0.63503 0.29137 0.8668 9 0.84037 0.12744 0.97452 0.57863 0.3364 0.82245 10 0.83918 0.12839 0.97414 0.51759 0.38513 0.76728 11 0.80931 0.15224 0.96364 0.45261 0.43701 0.70036 12 0.78026 0.17542 0.95172 0.38352 0.49217 0.61995 13 0.76719 0.18587 0.9458 0.30976 0.55105 0.52357 14 0.78197 0.17407 0.95246 0.23128 0.61371 0.40906 15 0.78109 0.17477 0.95208 0.14679 0.68116 0.27203 16 0.76813 0.18511 0.94624 0.056046 0.7536 0.10895 17 0.76411 0.18832 0.94436 -0.041685 0.83163 -0.085108 18 0.7803 0.1754 0.95173 -0.14672 0.91548 -0.31497 19 0.79388 0.16455 0.95751 -0.2607 1.0065 -0.58935 20 0.79486 0.16377 0.95792 -0.38339 1.1044 -0.91375 21 0.79181 0.16621 0.95666 -0.5162 1.2105 -1.2989 22 0.78394 0.17249 0.95332 -0.65872 1.3242 -1.7514 23 0.78403 0.17242 0.95336 -0.81111 1.4459 -2.2801 24 0.78649 0.17045 0.95442 -0.97414 1.576 -2.8972 25 0.78596 0.17088 0.95419 -1.1485 1.7153 -3.6161 26 0.78233 0.17378 0.95262 -1.3351 1.8642 -4.4528 27 0.77887 0.17654 0.9511 -1.5355 2.0242 -5.4286 28 0.78185 0.17416 0.95241 -1.7519 2.197 -6.5731 29 0.77716 0.17791 0.95034 -1.987 2.3846 -7.9219 30 0.77319 0.18107 0.94856 -2.2415 2.5879 -9.5076 Dati(1,5).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 87.5% 68.75% fit rms cod fit rms cod 1 0.9301 0.054591 0.99511 0.94772 0.04083 0.99727 2 0.88856 0.087037 0.98758 0.91736 0.064543 0.99317 3 0.87394 0.098455 0.98411 0.89727 0.080235 0.98945 4 0.86 0.10935 0.9804 0.88212 0.092068 0.9861 5 0.82558 0.13622 0.96958 0.87369 0.098648 0.98405 6 0.81512 0.1444 0.96582 0.87881 0.094651 0.98531 7 0.82753 0.1347 0.97025 0.90267 0.076017 0.99053 8 0.82913 0.13346 0.9708 0.91484 0.066509 0.99275 9 0.79894 0.15704 0.95957 0.90989 0.070377 0.99188 10 0.80711 0.15065 0.96279 0.90186 0.076651 0.99037 11 0.82879 0.13372 0.97069 0.90143 0.076982 0.99028 12 0.83117 0.13186 0.9715 0.89796 0.079695 0.98959 13 0.81963 0.14087 0.96747 0.89303 0.083548 0.98856 14 0.83076 0.13218 0.97136 0.90373 0.075192 0.99073 15 0.83952 0.12534 0.97425 0.91805 0.064007 0.99328 16 0.83841 0.12621 0.97389 0.91909 0.063193 0.99345 17 0.83241 0.13089 0.97191 0.91921 0.063101 0.99347 18 0.8367 0.12754 0.97333 0.9192 0.063111 0.99347 19 0.83437 0.12936 0.97257 0.9189 0.063342 0.99342 20 0.83633 0.12783 0.97321 0.91375 0.067362 0.99256 21 0.83421 0.12949 0.97251 0.89982 0.078247 0.98996 22 0.83416 0.12953 0.9725 0.89911 0.078799 0.98982 23 0.83068 0.13224 0.97133 0.90872 0.071292 0.99167 24 0.83418 0.12951 0.9725 0.91125 0.069312 0.99212 25 0.83146 0.13163 0.97159 0.91127 0.069297 0.99213 26 0.83035 0.1325 0.97122 0.91137 0.069226 0.99214 27 0.82866 0.13382 0.97064 0.91119 0.069361 0.99211 28 0.82948 0.13318 0.97092 0.90379 0.075141 0.99074 29 0.82794 0.13438 0.9704 0.8821 0.092083 0.9861 30 0.82464 0.13696 0.96925 0.8779 0.095366 0.98509 Dati(1,6).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 93.75% 62.5% fit rms cod fit rms cod 1 0.88181 0.095328 0.98603 0.96746 0.026243 0.99894 2 0.81453 0.1496 0.9656 0.95134 0.039246 0.99763 3 0.77273 0.18332 0.94835 0.93672 0.05104 0.996 4 0.75576 0.197 0.94035 0.92383 0.061439 0.9942 5 0.7025 0.23996 0.91149 0.91135 0.071507 0.99214 6 0.63972 0.2906 0.8702 0.90107 0.079797 0.99021 7 0.58851 0.33191 0.83068 0.89237 0.086817 0.98842 8 0.54048 0.37064 0.78885 0.8846 0.093085 0.98668 9 0.49487 0.40744 0.74484 0.87744 0.098857 0.98498 10 0.44783 0.44538 0.69511 0.87145 0.10369 0.98347 11 0.37485 0.50425 0.60919 0.86638 0.10778 0.98215 12 0.28236 0.57885 0.48499 0.86221 0.11114 0.98101 13 0.19403 0.65009 0.35042 0.85882 0.11388 0.98007 14 0.15593 0.68083 0.28754 0.85611 0.11606 0.9793 15 0.1033 0.72328 0.19592 0.85378 0.11794 0.97862 16 0.033804 0.77933 0.066466 0.85188 0.11947 0.97806 17 -0.068017 0.86146 -0.14066 0.85017 0.12085 0.97755 18 -0.1075 0.89331 -0.22656 0.84878 0.12197 0.97713 19 -0.14474 0.92335 -0.31044 0.84761 0.12292 0.97678 20 -0.18622 0.9568 -0.40712 0.84664 0.1237 0.97648 21 -0.23781 0.99842 -0.53218 0.84589 0.12431 0.97625 22 -0.29253 1.0426 -0.67063 0.84533 0.12476 0.97608 23 -0.32959 1.0724 -0.7678 0.84492 0.12509 0.97595 24 -0.35949 1.0966 -0.84822 0.84462 0.12533 0.97586 25 -0.38156 1.1144 -0.90872 0.8444 0.1255 0.97579 26 -0.39913 1.1285 -0.95756 0.84426 0.12562 0.97575 27 -0.43221 1.1552 -1.0512 0.84417 0.12569 0.97572 28 -0.44326 1.1641 -1.083 0.84412 0.12573 0.9757 29 -0.4389 1.1606 -1.0704 0.8441 0.12574 0.9757 30 -0.41059 1.1378 -0.98976 0.84411 0.12574 0.9757 Dati(1,7).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 84.375% 62.5% fit rms cod fit rms cod 1 0.9521 0.037379 0.99771 0.96196 0.029681 0.99855 2 0.89361 0.083015 0.98868 0.92838 0.055889 0.99487 3 0.831 0.13187 0.97144 0.89615 0.081037 0.98921 4 0.77257 0.17746 0.94828 0.86725 0.10359 0.98238 5 0.72085 0.21782 0.92208 0.84744 0.11905 0.97672 6 0.68187 0.24824 0.8988 0.83556 0.12831 0.97296 7 0.65832 0.26661 0.88326 0.83004 0.13262 0.97111 8 0.65045 0.27275 0.87782 0.82934 0.13317 0.97088 9 0.65614 0.26831 0.88176 0.83141 0.13156 0.97158 10 0.67196 0.25597 0.89239 0.83467 0.12901 0.97267 11 0.69321 0.23939 0.90588 0.83808 0.12635 0.97378 12 0.71476 0.22257 0.91864 0.84091 0.12414 0.97469 13 0.7332 0.20818 0.92882 0.84299 0.12252 0.97535 14 0.74622 0.19803 0.9356 0.84422 0.12156 0.97573 15 0.75402 0.19194 0.93949 0.84479 0.12111 0.97591 16 0.75777 0.18901 0.94133 0.84487 0.12105 0.97594 17 0.75904 0.18802 0.94194 0.84466 0.12121 0.97587 18 0.75868 0.1883 0.94177 0.84432 0.12148 0.97576 19 0.75696 0.18965 0.94093 0.84396 0.12176 0.97565 20 0.75389 0.19204 0.93943 0.84365 0.122 0.97556 21 0.74939 0.19555 0.93719 0.84344 0.12217 0.97549 22 0.74405 0.19972 0.93449 0.8433 0.12227 0.97545 23 0.73868 0.20391 0.93171 0.84324 0.12232 0.97543 24 0.73412 0.20747 0.92931 0.84323 0.12233 0.97542 25 0.73087 0.21001 0.92757 0.84326 0.12231 0.97543 26 0.72933 0.21121 0.92674 0.84329 0.12228 0.97544 27 0.72941 0.21115 0.92678 0.84333 0.12225 0.97545 28 0.73069 0.21014 0.92747 0.84336 0.12223 0.97546 29 0.73272 0.20856 0.92856 0.84338 0.12221 0.97547 30 0.73494 0.20683 0.92974 0.8434 0.1222 0.97548 Dati(1,8).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 90.625% 62.5% fit rms cod fit rms cod 1 0.91648 0.066002 0.99302 0.9589 0.032476 0.99831 2 0.87129 0.10171 0.98343 0.94973 0.039728 0.99747 3 0.84497 0.12251 0.97596 0.93917 0.048068 0.9963 4 0.8197 0.14248 0.96749 0.93553 0.050947 0.99584 5 0.79529 0.16177 0.95809 0.91957 0.06356 0.99353 6 0.79489 0.16208 0.95793 0.9106 0.070645 0.99201 7 0.78273 0.17169 0.95279 0.89664 0.081678 0.98932 8 0.77583 0.17715 0.94975 0.88953 0.087298 0.9878 9 0.73806 0.20699 0.93139 0.87252 0.10074 0.98375 10 0.71321 0.22662 0.91775 0.86183 0.10918 0.98091 11 0.69144 0.24383 0.90479 0.84645 0.12134 0.97642 12 0.68154 0.25165 0.89858 0.83711 0.12872 0.97347 13 0.66899 0.26157 0.89044 0.82063 0.14174 0.96783 14 0.67436 0.25733 0.89396 0.80924 0.15074 0.96361 15 0.67038 0.26047 0.89135 0.79263 0.16387 0.957 16 0.67129 0.25976 0.89195 0.78125 0.17286 0.95215 17 0.65736 0.27076 0.8826 0.76438 0.18619 0.94448 18 0.65012 0.27648 0.87759 0.75155 0.19633 0.93827 19 0.63948 0.28489 0.87003 0.73419 0.21005 0.92934 20 0.63837 0.28577 0.86923 0.72115 0.22035 0.92224 21 0.63384 0.28935 0.86593 0.70374 0.23411 0.91223 22 0.63915 0.28516 0.86978 0.68984 0.24509 0.9038 23 0.63865 0.28555 0.86943 0.67196 0.25923 0.89239 24 0.64146 0.28332 0.87145 0.65749 0.27066 0.88269 25 0.63733 0.28659 0.86847 0.63934 0.285 0.86993 26 0.63659 0.28717 0.86794 0.62413 0.29702 0.85872 27 0.63257 0.29035 0.86499 0.60552 0.31173 0.84438 28 0.63327 0.2898 0.86551 0.58963 0.32428 0.8316 29 0.63166 0.29107 0.86433 0.57034 0.33953 0.81539 30 0.63422 0.28905 0.86621 0.55354 0.3528 0.80068 Dati(1,9).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 56.25% 78.125% fit rms cod fit rms cod 1 0.88029 0.11672 0.98567 0.8771 0.11983 0.9849 2 0.81127 0.18402 0.96438 0.79283 0.202 0.95708 3 0.7645 0.22962 0.94454 0.73892 0.25457 0.93184 4 0.7317 0.2616 0.92802 0.70037 0.29215 0.91022 5 0.7036 0.289 0.91215 0.66984 0.32192 0.89099 6 0.67984 0.31217 0.8975 0.6551 0.33629 0.88104 7 0.66134 0.33021 0.88531 0.65545 0.33595 0.88128 8 0.64747 0.34373 0.87573 0.65845 0.33302 0.88335 9 0.63699 0.35395 0.86822 0.66507 0.32657 0.88782 10 0.62935 0.3614 0.86262 0.67022 0.32155 0.89124 11 0.62382 0.36679 0.85849 0.67326 0.31859 0.89324 12 0.61991 0.3706 0.85553 0.67557 0.31633 0.89475 13 0.61701 0.37343 0.85332 0.67628 0.31564 0.89521 14 0.61503 0.37537 0.85179 0.67692 0.31502 0.89562 15 0.61364 0.37672 0.85073 0.67723 0.31472 0.89582 16 0.61271 0.37762 0.85001 0.67677 0.31516 0.89552 17 0.61211 0.37821 0.84954 0.67443 0.31745 0.894 18 0.61173 0.37858 0.84925 0.671 0.32079 0.89176 19 0.61146 0.37884 0.84904 0.66757 0.32413 0.88949 20 0.61128 0.37902 0.8489 0.66487 0.32676 0.88769 21 0.61116 0.37913 0.84881 0.66257 0.32901 0.88614 22 0.6111 0.3792 0.84875 0.66188 0.32968 0.88567 23 0.61105 0.37924 0.84872 0.66223 0.32934 0.88591 24 0.61102 0.37927 0.84869 0.66182 0.32974 0.88564 25 0.61099 0.3793 0.84867 0.65927 0.33223 0.8839 26 0.61097 0.37932 0.84866 0.65546 0.33594 0.88129 27 0.61095 0.37933 0.84864 0.65171 0.33959 0.8787 28 0.61094 0.37935 0.84863 0.64952 0.34173 0.87716 29 0.61093 0.37936 0.84862 0.65088 0.34041 0.87811 30 0.61091 0.37938 0.84861 0.65555 0.33585 0.88135 Dati(1,10).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 90.625% 71.875% fit rms cod fit rms cod 1 0.92477 0.064758 0.99434 0.96321 0.031672 0.99865 2 0.87 0.1119 0.9831 0.95191 0.041396 0.99769 3 0.82798 0.14807 0.97041 0.94275 0.049279 0.99672 4 0.80066 0.17159 0.96026 0.93605 0.055046 0.99591 5 0.787 0.18334 0.95463 0.93309 0.057598 0.99552 6 0.76901 0.19883 0.94664 0.93134 0.059101 0.99529 7 0.75564 0.21034 0.94029 0.93045 0.059868 0.99516 8 0.74168 0.22236 0.93327 0.93 0.060257 0.9951 9 0.71707 0.24354 0.91995 0.92983 0.060403 0.99508 10 0.69403 0.26338 0.90638 0.92982 0.060409 0.99507 11 0.66801 0.28577 0.88978 0.92985 0.060387 0.99508 12 0.64726 0.30363 0.87557 0.92988 0.060362 0.99508 13 0.63655 0.31285 0.8679 0.92989 0.060351 0.99508 14 0.62808 0.32014 0.86167 0.92989 0.060348 0.99508 15 0.62163 0.3257 0.85683 0.92989 0.06035 0.99508 16 0.61743 0.32931 0.85364 0.92988 0.060354 0.99508 17 0.60221 0.34241 0.84176 0.92988 0.060357 0.99508 18 0.5917 0.35145 0.83329 0.92988 0.060361 0.99508 19 0.58047 0.36112 0.824 0.92987 0.060364 0.99508 20 0.57683 0.36425 0.82093 0.92987 0.060365 0.99508 21 0.57382 0.36685 0.81837 0.92987 0.060366 0.99508 22 0.57459 0.36618 0.81903 0.92987 0.060366 0.99508 23 0.57306 0.3675 0.81772 0.92987 0.060366 0.99508 24 0.57194 0.36847 0.81676 0.92987 0.060366 0.99508 25 0.56501 0.37443 0.81078 0.92987 0.060366 0.99508 26 0.56052 0.37829 0.80686 0.92987 0.060366 0.99508 27 0.5569 0.38141 0.80366 0.92987 0.060366 0.99508 28 0.55536 0.38274 0.80229 0.92987 0.060366 0.99508 29 0.55608 0.38212 0.80293 0.92987 0.060366 0.99508 30 0.55662 0.38165 0.80342 0.92987 0.060366 0.99508 Dati(1,11).t.glar_norm.mod(p,n).Mgl n=200 n=500 Sparsità: 93.75% 78.125% fit rms cod fit rms cod 1 0.8853 0.08114 0.98684 0.95876 0.029175 0.9983 2 0.77474 0.15935 0.94926 0.94516 0.038796 0.99699 3 0.70236 0.21055 0.91141 0.92704 0.051616 0.99468 4 0.62256 0.267 0.85754 0.91459 0.060421 0.9927 5 0.56128 0.31035 0.80752 0.90094 0.070076 0.99019 6 0.54942 0.31874 0.79698 0.89843 0.071854 0.98968 7 0.5417 0.3242 0.78997 0.89313 0.075602 0.98858 8 0.53182 0.33119 0.78081 0.89191 0.076461 0.98832 9 0.52926 0.33301 0.7784 0.88811 0.079149 0.98748 10 0.53529 0.32874 0.78405 0.88798 0.079242 0.98745 11 0.54694 0.3205 0.79474 0.88493 0.081403 0.98676 12 0.56431 0.30821 0.81018 0.88511 0.081273 0.9868 13 0.579 0.29782 0.82276 0.8833 0.082556 0.98638 14 0.59308 0.28786 0.83442 0.88422 0.081902 0.9866 15 0.61114 0.27509 0.84879 0.88343 0.082466 0.98641 16 0.62392 0.26604 0.85857 0.88436 0.081806 0.98663 17 0.63178 0.26048 0.86442 0.88297 0.082786 0.9863 18 0.63992 0.25472 0.87034 0.88363 0.082325 0.98646 19 0.64569 0.25064 0.87446 0.88218 0.083346 0.98612 20 0.64258 0.25284 0.87225 0.88317 0.082647 0.98635 21 0.63781 0.25622 0.86882 0.88022 0.084737 0.98565 22 0.63466 0.25845 0.86653 0.88131 0.083962 0.98591 23 0.62832 0.26293 0.86185 0.87698 0.087022 0.98487 24 0.61949 0.26918 0.85521 0.87885 0.085702 0.98532 25 0.61328 0.27357 0.85045 0.87229 0.09034 0.98369 26 0.61045 0.27557 0.84825 0.87383 0.089257 0.98408 27 0.60983 0.27601 0.84777 0.86737 0.093822 0.98241 28 0.61291 0.27383 0.85016 0.8692 0.092531 0.98289 29 0.61714 0.27084 0.85342 0.86098 0.098344 0.98067 30 0.62258 0.26699 0.85755 0.86418 0.096078 0.98155