Dati(1,1).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 96.875% 87.5% fit rms cod fit rms cod 1 0.89234 0.073775 0.98841 0.90498 0.065118 0.99097 2 0.88308 0.080124 0.98633 0.84098 0.10898 0.97471 3 0.85585 0.098782 0.97922 0.78656 0.14627 0.95444 4 0.84008 0.10959 0.97442 0.75387 0.16867 0.93942 5 0.80738 0.132 0.9629 0.72024 0.19171 0.92173 6 0.798 0.13843 0.9592 0.67951 0.21963 0.89728 7 0.77792 0.15218 0.95068 0.64955 0.24016 0.87719 8 0.77662 0.15308 0.9501 0.62652 0.25594 0.86051 9 0.73929 0.17866 0.93203 0.60256 0.27236 0.84204 10 0.73834 0.17931 0.93154 0.57198 0.29331 0.8168 11 0.6982 0.20682 0.90892 0.55078 0.30784 0.79821 12 0.71346 0.19636 0.91789 0.52888 0.32285 0.77804 13 0.67877 0.22013 0.89681 0.49998 0.34265 0.74998 14 0.69627 0.20814 0.90775 0.46509 0.36656 0.71387 15 0.66946 0.22651 0.89074 0.42933 0.39107 0.67434 16 0.68824 0.21364 0.9028 0.40102 0.41047 0.64122 17 0.62932 0.25402 0.8626 0.36973 0.43191 0.60276 18 0.65968 0.23322 0.88418 0.33739 0.45407 0.56095 19 0.61355 0.26483 0.85066 0.30501 0.47626 0.51699 20 0.63614 0.24935 0.8676 0.27721 0.49532 0.47757 21 0.57052 0.29431 0.81555 0.24843 0.51503 0.43515 22 0.59853 0.27512 0.83882 0.21894 0.53525 0.38994 23 0.54344 0.31287 0.79156 0.18955 0.55538 0.34317 24 0.54372 0.31268 0.79181 0.16218 0.57414 0.29806 25 0.43841 0.38484 0.68462 0.13459 0.59305 0.25107 26 0.44811 0.3782 0.69541 0.10481 0.61346 0.19863 27 0.34211 0.45084 0.56718 0.074469 0.63425 0.14339 28 0.31993 0.46604 0.53751 0.045289 0.65424 0.088526 29 0.17939 0.56235 0.3266 0.016033 0.67429 0.031809 30 0.14462 0.58617 0.26833 -0.014131 0.69496 -0.028462 Dati(1,2).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 93.75% fit rms cod fit rms cod 1 -0.12179 0.86041 -0.25842 0.78506 0.16486 0.9538 2 -0.48459 1.1387 -1.204 0.74208 0.19782 0.93348 3 -1.0819 1.5968 -3.3344 0.7468 0.1942 0.93589 4 -0.84427 1.4145 -2.4013 0.72829 0.2084 0.92617 5 -0.24393 0.9541 -0.54737 0.62298 0.28918 0.85785 6 0.17619 0.63186 0.32134 0.56213 0.33585 0.80827 7 0.47219 0.40483 0.72142 0.53214 0.35885 0.78111 8 0.20722 0.60806 0.3715 0.55097 0.3444 0.79837 9 -0.23923 0.95049 -0.53569 0.49894 0.38431 0.74894 10 -0.39591 1.0707 -0.94855 0.44108 0.42869 0.68761 11 -0.53544 1.1777 -1.3576 0.4093 0.45306 0.65108 12 0.04361 0.73355 0.085317 0.42154 0.44368 0.66538 13 0.21262 0.60392 0.38004 0.40296 0.45793 0.64355 14 0.28528 0.54819 0.48917 0.36895 0.48401 0.60178 15 0.1807 0.62841 0.32874 0.33414 0.51071 0.55663 16 -0.29355 0.99215 -0.67326 0.33602 0.50927 0.55913 17 -0.43207 1.0984 -1.0508 0.33427 0.51061 0.5568 18 -0.46761 1.1257 -1.1539 0.31787 0.52319 0.5347 19 -0.1079 0.84976 -0.22745 0.29038 0.54428 0.49643 20 0.127 0.66959 0.23788 0.28451 0.54878 0.48807 21 0.12501 0.67111 0.2344 0.28558 0.54796 0.4896 22 0.11126 0.68167 0.21014 0.28117 0.55134 0.48329 23 -0.19483 0.91643 -0.42761 0.26393 0.56456 0.45821 24 -0.39558 1.0704 -0.94765 0.25484 0.57154 0.44474 25 -0.31656 1.0098 -0.73332 0.25428 0.57197 0.4439 26 -0.12807 0.86523 -0.27254 0.25502 0.5714 0.44501 27 0.026344 0.74679 0.051993 0.24654 0.57791 0.43229 28 0.023663 0.74885 0.046766 0.23856 0.58402 0.42021 29 0.027902 0.7456 0.055025 0.23588 0.58608 0.41612 30 -0.10052 0.8441 -0.21115 0.23741 0.58491 0.41845 Dati(1,3).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 71.875% 68.75% fit rms cod fit rms cod 1 0.88876 0.094744 0.98763 0.92129 0.067039 0.9938 2 0.9147 0.072651 0.99272 0.87479 0.10665 0.98432 3 0.90491 0.080993 0.99096 0.84205 0.13453 0.97505 4 0.90809 0.07828 0.99155 0.82278 0.15095 0.96859 5 0.90649 0.079642 0.99126 0.80278 0.16797 0.96111 6 0.90683 0.079352 0.99132 0.7976 0.17239 0.95903 7 0.90668 0.079481 0.99129 0.80756 0.16391 0.96297 8 0.90673 0.079443 0.9913 0.82738 0.14703 0.9702 9 0.9067 0.079463 0.9913 0.84581 0.13132 0.97623 10 0.90671 0.079459 0.9913 0.86287 0.1168 0.9812 11 0.90671 0.079461 0.9913 0.87635 0.10532 0.98471 12 0.90671 0.079461 0.9913 0.88351 0.099218 0.98643 13 0.90671 0.079461 0.9913 0.88516 0.097814 0.98681 14 0.90671 0.079461 0.9913 0.88384 0.098935 0.98651 15 0.90671 0.079461 0.9913 0.87946 0.10266 0.98547 16 0.90671 0.079461 0.9913 0.87237 0.10871 0.98371 17 0.90671 0.079461 0.9913 0.8634 0.11635 0.98134 18 0.90671 0.079461 0.9913 0.85403 0.12433 0.97869 19 0.90671 0.079461 0.9913 0.84679 0.1305 0.97653 20 0.90671 0.079461 0.9913 0.84316 0.13358 0.9754 21 0.90671 0.079461 0.9913 0.84297 0.13375 0.97534 22 0.90671 0.079461 0.9913 0.84577 0.13136 0.97621 23 0.90671 0.079461 0.9913 0.85032 0.12749 0.9776 24 0.90671 0.079461 0.9913 0.85546 0.1231 0.97911 25 0.90671 0.079461 0.9913 0.85991 0.11932 0.98038 26 0.90671 0.079461 0.9913 0.86285 0.11681 0.98119 27 0.90671 0.079461 0.9913 0.86443 0.11547 0.98162 28 0.90671 0.079461 0.9913 0.86491 0.11506 0.98175 29 0.90671 0.079461 0.9913 0.86443 0.11547 0.98162 30 0.90671 0.079461 0.9913 0.86315 0.11656 0.98127 Dati(1,4).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 62.5% fit rms cod fit rms cod 1 -0.60196 1.2789 -1.5663 0.89746 0.081865 0.98948 2 -1.4472 1.9537 -4.9888 0.81449 0.1481 0.96559 3 -1.138 1.7068 -3.5709 0.75093 0.19884 0.93797 4 -0.31863 1.0527 -0.73877 0.70072 0.23893 0.91043 5 0.26686 0.5853 0.4625 0.63881 0.28835 0.86954 6 0.07269 0.74031 0.1401 0.56412 0.34798 0.81001 7 0.25271 0.59659 0.44156 0.48416 0.41182 0.73391 8 0.44865 0.44017 0.69602 0.40399 0.47582 0.64477 9 -0.033048 0.82473 -0.067188 0.32176 0.54147 0.53999 10 0.47002 0.42311 0.71912 0.23425 0.61133 0.41363 11 -0.67142 1.3344 -1.7936 0.14079 0.68595 0.26175 12 -1.6101 2.0838 -5.8126 0.042194 0.76466 0.082607 13 -1.3636 1.887 -4.5868 -0.061076 0.84711 -0.12588 14 -0.1907 0.95059 -0.41777 -0.16972 0.93384 -0.36825 15 -0.094708 0.87396 -0.19839 -0.28469 1.0256 -0.65042 16 -0.39866 1.1166 -0.95625 -0.40632 1.1227 -0.97774 17 -0.20769 0.96415 -0.45852 -0.5348 1.2253 -1.3556 18 -0.22413 0.97728 -0.49848 -0.67022 1.3334 -1.7896 19 -1.3186 1.851 -4.3758 -0.81293 1.4473 -2.2867 20 -0.27688 1.0194 -0.63041 -0.96371 1.5677 -2.8561 21 -0.59787 1.2757 -1.5532 -1.1231 1.6949 -3.5074 22 -1.9379 2.3454 -7.6311 -1.2918 1.8296 -4.2523 23 -0.95832 1.5634 -2.835 -1.4705 1.9723 -5.1032 24 -0.065167 0.85037 -0.13458 -1.6596 2.1233 -6.0736 25 -0.30998 1.0458 -0.71605 -1.8598 2.2831 -7.1785 26 -1.1775 1.7384 -3.7417 -2.0716 2.4522 -8.435 27 -0.72748 1.3791 -1.9842 -2.2957 2.6311 -9.8616 28 -1.1748 1.7363 -3.7299 -2.5327 2.8203 -11.4798 29 -2.8297 3.0574 -13.6666 -2.7834 3.0204 -13.3139 30 -1.1972 1.7542 -3.8279 -3.0486 3.2322 -15.3913 Dati(1,5).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 96.875% fit rms cod fit rms cod 1 0.59073 0.31965 0.8325 0.52834 0.36838 0.77754 2 0.37979 0.4844 0.61535 0.36142 0.49875 0.59221 3 0.34318 0.51299 0.56859 0.13236 0.67765 0.24721 4 0.2634 0.57531 0.45742 -0.039953 0.81223 -0.081501 5 0.010018 0.7732 0.019936 -0.15483 0.90195 -0.33363 6 -0.079026 0.84275 -0.1643 -0.20516 0.94126 -0.4524 7 0.022232 0.76366 0.043971 -0.075522 0.84001 -0.15675 8 0.00045526 0.78067 0.00091032 -0.028601 0.80336 -0.05802 9 -0.21616 0.94985 -0.47905 -0.040416 0.81259 -0.082466 10 -0.13308 0.88497 -0.28388 -0.06168 0.8292 -0.12716 11 0.0031494 0.77857 0.0062888 0.012367 0.77137 0.024581 12 -0.061661 0.82919 -0.12712 0.00076328 0.78043 0.001526 13 -0.20941 0.94458 -0.46266 -0.0018987 0.78251 -0.003801 14 -0.075255 0.8398 -0.15617 0.035651 0.75318 0.07003 15 0.048701 0.74299 0.095031 0.11958 0.68763 0.22486 16 -0.073607 0.83852 -0.15263 0.18789 0.63428 0.34048 17 -0.17763 0.91976 -0.3868 0.18485 0.63665 0.33553 18 0.0033666 0.7784 0.0067219 0.20177 0.62344 0.36284 19 0.052277 0.7402 0.10182 0.2187 0.61022 0.38957 20 -0.099137 0.85846 -0.2081 0.21503 0.61309 0.38382 21 -0.13647 0.88761 -0.29156 0.18158 0.63921 0.33018 22 0.037772 0.75153 0.074118 0.16927 0.64882 0.30989 23 0.030486 0.75722 0.060042 0.17964 0.64073 0.327 24 -0.1343 0.88592 -0.28665 0.18211 0.63879 0.33106 25 -0.095367 0.85551 -0.19983 0.16953 0.64862 0.31032 26 0.044904 0.74596 0.087792 0.16194 0.65455 0.29765 27 -0.0091238 0.78815 -0.018331 0.17106 0.64743 0.31285 28 -0.15585 0.90275 -0.33598 0.16475 0.65235 0.30236 29 -0.053331 0.82268 -0.10951 0.14742 0.66589 0.2731 30 0.030221 0.75742 0.059529 0.13764 0.67353 0.25633 Dati(1,6).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 75% fit rms cod fit rms cod 1 0.6925 0.24803 0.90545 0.94658 0.043088 0.99715 2 0.51532 0.39094 0.76509 0.91893 0.065394 0.99343 3 0.38862 0.49314 0.62622 0.89438 0.08519 0.98885 4 0.30331 0.56195 0.51462 0.87372 0.10186 0.98405 5 0.073349 0.74744 0.14132 0.85087 0.12029 0.97776 6 -0.18765 0.95796 -0.41052 0.83227 0.13529 0.97187 7 -0.41733 1.1432 -1.0088 0.81601 0.14841 0.96615 8 -0.67557 1.3515 -1.8075 0.8017 0.15995 0.96068 9 -0.94869 1.5718 -2.7974 0.78823 0.17081 0.95515 10 -1.2634 1.8257 -4.1231 0.77675 0.18007 0.95016 11 -1.7395 2.2097 -6.5051 0.76675 0.18814 0.94559 12 -2.3336 2.6889 -10.1128 0.75817 0.19506 0.94152 13 -2.9766 3.2075 -14.8131 0.75064 0.20113 0.93782 14 -3.5241 3.6491 -19.4674 0.74427 0.20627 0.9346 15 -4.2259 4.2152 -26.3105 0.73867 0.21079 0.93171 16 -5.083 4.9065 -36.0027 0.73387 0.21466 0.92918 17 -6.0733 5.7053 -49.0319 0.7297 0.21803 0.92694 18 -7.0078 6.4591 -63.1246 0.72616 0.22088 0.92501 19 -8.0793 7.3233 -81.4335 0.72314 0.22332 0.92335 20 -9.3442 8.3436 -106.0015 0.72061 0.22535 0.92194 21 -10.7854 9.5061 -137.8967 0.71851 0.22705 0.92076 22 -12.4277 10.8307 -179.3018 0.71683 0.22841 0.91981 23 -14.2702 12.3169 -232.1803 0.7155 0.22947 0.91906 24 -16.316 13.967 -298.8422 0.71446 0.23031 0.91847 25 -18.5707 15.7857 -382.0104 0.71368 0.23094 0.91802 26 -21.0767 17.807 -486.382 0.71307 0.23144 0.91767 27 -23.9603 20.133 -622.0181 0.71263 0.23179 0.91742 28 -27.0612 22.6341 -786.4332 0.71233 0.23204 0.91724 29 -30.4812 25.3927 -990.068 0.7121 0.23222 0.91711 30 -34.262 28.4422 -1242.407 0.71196 0.23234 0.91703 Dati(1,7).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 90.625% 96.875% fit rms cod fit rms cod 1 0.91068 0.069695 0.99202 0.84006 0.12481 0.97442 2 0.78935 0.16438 0.95562 0.66607 0.26057 0.88849 3 0.66245 0.26339 0.88606 0.50746 0.38433 0.7574 4 0.55421 0.34785 0.80127 0.35732 0.50149 0.58696 5 0.4785 0.40693 0.72804 0.23872 0.59403 0.42046 6 0.44431 0.43361 0.69121 0.15488 0.65945 0.28577 7 0.45137 0.4281 0.699 0.10095 0.70154 0.1917 8 0.49188 0.39649 0.74181 0.073729 0.72278 0.14202 9 0.55297 0.34882 0.80017 0.066854 0.72814 0.12924 10 0.62011 0.29643 0.85568 0.073489 0.72296 0.14158 11 0.67918 0.25034 0.89708 0.08803 0.71162 0.16831 12 0.72038 0.21819 0.92181 0.10576 0.69778 0.20033 13 0.74087 0.2022 0.93285 0.1233 0.68409 0.23141 14 0.74244 0.20098 0.93366 0.13859 0.67217 0.25797 15 0.72836 0.21197 0.92621 0.15057 0.66282 0.27847 16 0.70248 0.23216 0.91148 0.15904 0.65621 0.29278 17 0.66998 0.25752 0.89108 0.16431 0.6521 0.30162 18 0.63745 0.2829 0.86856 0.16695 0.65004 0.30603 19 0.61099 0.30355 0.84867 0.16765 0.64949 0.30719 20 0.59496 0.31606 0.83594 0.16707 0.64995 0.30622 21 0.59079 0.31931 0.83255 0.16576 0.65096 0.30405 22 0.59739 0.31416 0.8379 0.16418 0.6522 0.3014 23 0.61156 0.3031 0.84911 0.16262 0.65342 0.29879 24 0.62912 0.2894 0.86245 0.16127 0.65447 0.29653 25 0.64621 0.27607 0.87483 0.16021 0.6553 0.29475 26 0.65977 0.26548 0.88425 0.15946 0.65588 0.2935 27 0.66822 0.25889 0.88992 0.159 0.65624 0.29273 28 0.67133 0.25647 0.89198 0.15877 0.65642 0.29234 29 0.66969 0.25774 0.8909 0.15871 0.65646 0.29223 30 0.66432 0.26193 0.88732 0.15876 0.65643 0.29231 Dati(1,8).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 68.75% fit rms cod fit rms cod 1 0.33642 0.52438 0.55966 0.89103 0.086107 0.98813 2 0.22199 0.6148 0.3947 0.8372 0.12865 0.9735 3 0.17469 0.65218 0.31886 0.78766 0.1678 0.95491 4 0.090535 0.71868 0.17287 0.76208 0.18801 0.94339 5 0.18525 0.64383 0.33619 0.6915 0.24378 0.90483 6 0.42148 0.45716 0.66531 0.64023 0.2843 0.87057 7 0.28963 0.56135 0.49537 0.58157 0.33065 0.82492 8 0.32623 0.53243 0.54603 0.54135 0.36243 0.78964 9 0.041023 0.7578 0.080363 0.47781 0.41265 0.72732 10 -0.099887 0.86916 -0.20975 0.42532 0.45413 0.66974 11 -0.15537 0.913 -0.33489 0.36479 0.50196 0.5965 12 -0.067886 0.84387 -0.14038 0.31623 0.54033 0.53246 13 -0.029189 0.81329 -0.059229 0.25546 0.58835 0.44566 14 0.19335 0.63743 0.34932 0.20124 0.6312 0.36199 15 0.13271 0.68535 0.2478 0.14018 0.67945 0.26071 16 0.13632 0.6825 0.25406 0.086338 0.722 0.16522 17 -0.016496 0.80326 -0.033264 0.025418 0.77014 0.05019 18 -0.096401 0.8664 -0.2021 -0.031349 0.81499 -0.063681 19 -0.1875 0.93839 -0.41016 -0.0929 0.86363 -0.19443 20 -0.05935 0.83712 -0.12222 -0.15013 0.90886 -0.32279 21 -0.043895 0.82491 -0.089716 -0.21156 0.9574 -0.46787 22 0.08959 0.71943 0.17115 -0.27055 1.004 -0.61431 23 0.069822 0.73505 0.13477 -0.33323 1.0535 -0.7775 24 0.0701 0.73483 0.13529 -0.39384 1.1014 -0.94279 25 -0.02948 0.81352 -0.059829 -0.4575 1.1518 -1.1243 26 -0.056096 0.83455 -0.11534 -0.51981 1.201 -1.3098 27 -0.14653 0.90602 -0.31454 -0.58457 1.2522 -1.5109 28 -0.042156 0.82354 -0.08609 -0.64819 1.3024 -1.7165 29 -0.031874 0.81541 -0.064764 -0.71388 1.3543 -1.9374 30 0.032564 0.76449 0.064068 -0.77876 1.4056 -2.164 Dati(1,9).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 56.25% 0% fit rms cod fit rms cod 1 0.8652 0.13143 0.98183 0.66708 0.32461 0.88916 2 0.79903 0.19595 0.95961 0.40055 0.58449 0.64066 3 0.75072 0.24306 0.93786 0.1736 0.80578 0.31706 4 0.71595 0.27696 0.91932 -0.073772 1.047 -0.15299 5 0.68554 0.30661 0.90112 -0.23431 1.2035 -0.52351 6 0.65942 0.33208 0.884 -0.28873 1.2566 -0.66081 7 0.63857 0.35241 0.86937 -0.26554 1.234 -0.6016 8 0.62209 0.36848 0.85718 -0.22442 1.1939 -0.49921 9 0.60908 0.38116 0.84718 -0.16524 1.1362 -0.35777 10 0.59935 0.39065 0.83948 -0.097456 1.0701 -0.20441 11 0.59205 0.39777 0.83357 -0.045847 1.0197 -0.093796 12 0.58639 0.40329 0.82893 -0.011089 0.98585 -0.022301 13 0.58191 0.40766 0.8252 0.020154 0.95539 0.039902 14 0.57834 0.41113 0.82221 0.046372 0.92983 0.090594 15 0.57554 0.41386 0.81984 0.057294 0.91918 0.1113 16 0.5733 0.41605 0.81793 0.063674 0.91296 0.12329 17 0.57151 0.41779 0.8164 0.051472 0.92485 0.10029 18 0.57011 0.41916 0.8152 0.020274 0.95527 0.040136 19 0.56896 0.42028 0.81421 -0.010586 0.98536 -0.021284 20 0.56802 0.4212 0.81339 -0.050191 1.024 -0.1029 21 0.56726 0.42194 0.81273 -0.098225 1.0708 -0.2061 22 0.56664 0.42254 0.8122 -0.11035 1.0826 -0.23287 23 0.56614 0.42303 0.81176 -0.10933 1.0816 -0.23062 24 0.56573 0.42343 0.81141 -0.090888 1.0637 -0.19004 25 0.56542 0.42373 0.81114 -0.063505 1.037 -0.13104 26 0.56517 0.42397 0.81093 -0.059348 1.0329 -0.12222 27 0.56498 0.42416 0.81076 -0.079222 1.0523 -0.16472 28 0.56482 0.42432 0.81062 -0.10999 1.0823 -0.23208 29 0.5647 0.42444 0.81051 -0.12248 1.0945 -0.25997 30 0.56459 0.42454 0.81042 -0.098776 1.0714 -0.20731 Dati(1,10).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 81.25% fit rms cod fit rms cod 1 0.39218 0.5232 0.63055 0.80657 0.1665 0.96258 2 0.28533 0.61517 0.48925 0.67126 0.28297 0.89193 3 0.27276 0.62599 0.47112 0.53969 0.39622 0.78812 4 0.57611 0.36487 0.82032 0.44442 0.47823 0.69133 5 0.68505 0.2711 0.90081 0.4289 0.49159 0.67384 6 0.69072 0.26622 0.90434 0.44433 0.47831 0.69123 7 0.48377 0.44436 0.73351 0.49139 0.4378 0.74132 8 -0.0049106 0.865 -0.0098452 0.54406 0.39246 0.79212 9 -0.46906 1.2645 -1.1581 0.58178 0.36 0.82509 10 -0.47879 1.2729 -1.1868 0.60459 0.34036 0.84365 11 -0.036336 0.89205 -0.073993 0.60912 0.33646 0.84721 12 0.32995 0.57676 0.55103 0.60171 0.34284 0.84136 13 0.3297 0.57698 0.5507 0.58874 0.354 0.83087 14 0.33094 0.57591 0.55236 0.57454 0.36623 0.81898 15 0.19397 0.69381 0.35032 0.5638 0.37547 0.80973 16 -0.43495 1.2352 -1.0591 0.55811 0.38037 0.80473 17 -1.0798 1.7903 -3.3258 0.55729 0.38107 0.80401 18 -0.49485 1.2867 -1.2346 0.55999 0.37875 0.80639 19 0.037625 0.82839 0.073835 0.56405 0.37526 0.80994 20 -0.44123 1.2406 -1.0771 0.56785 0.37199 0.81325 21 -0.50016 1.2913 -1.2505 0.57046 0.36973 0.8155 22 -0.10721 0.95306 -0.22591 0.57165 0.36872 0.81651 23 -0.19118 1.0253 -0.4189 0.57167 0.3687 0.81653 24 -1.233 1.9221 -3.9861 0.57097 0.3693 0.81593 25 -1.8041 2.4137 -6.863 0.57001 0.37012 0.81511 26 -0.59953 1.3768 -1.5585 0.56916 0.37086 0.81437 27 -0.45471 1.2522 -1.1162 0.56859 0.37135 0.81389 28 -1.8114 2.42 -6.9039 0.56836 0.37154 0.81369 29 -1.5349 2.182 -5.4259 0.56839 0.37152 0.81372 30 -0.22435 1.0539 -0.49903 0.56857 0.37137 0.81386 Dati(1,11).t.glar_norm.mod(p,n).Mgls n=200 n=500 Sparsità: 0% 0% fit rms cod fit rms cod 1 0.53455 0.32927 0.78335 0.67259 0.23161 0.8928 2 0.017089 0.69532 0.033887 0.57505 0.30061 0.81942 3 -0.24541 0.88101 -0.55105 0.36747 0.44746 0.5999 4 -0.48194 1.0483 -1.1961 0.25205 0.52911 0.44057 5 -0.68976 1.1954 -1.8553 0.09503 0.64018 0.18103 6 -0.67466 1.1847 -1.8045 0.13472 0.61211 0.25129 7 -0.57264 1.1125 -1.4732 0.056758 0.66726 0.1103 8 -0.49996 1.0611 -1.2499 0.10691 0.63178 0.20239 9 -0.47654 1.0445 -1.1802 0.033407 0.68378 0.065697 10 -0.44298 1.0208 -1.0822 0.10493 0.63318 0.19885 11 -0.36793 0.96769 -0.87123 -0.0064108 0.71194 -0.012863 12 -0.2789 0.90471 -0.63559 0.083738 0.64817 0.16046 13 -0.23803 0.87579 -0.53272 -2.9241e-06 0.70741 -5.8482e-06 14 -0.1989 0.84812 -0.43737 0.12354 0.62002 0.23182 15 -0.07851 0.76295 -0.16318 0.045238 0.67541 0.08843 16 0.036602 0.68152 0.071864 0.1563 0.59684 0.28818 17 0.068555 0.65891 0.13241 0.047058 0.67412 0.091902 18 0.068708 0.6588 0.1327 0.14808 0.60265 0.27424 19 0.069409 0.65831 0.134 0.02326 0.69095 0.045978 20 0.0073669 0.7022 0.014679 0.14692 0.60348 0.27225 21 -0.096571 0.77572 -0.20247 0.0084755 0.70141 0.016879 22 -0.18253 0.83654 -0.39839 0.1166 0.62493 0.2196 23 -0.2676 0.89671 -0.60682 -0.055239 0.74649 -0.11353 24 -0.33393 0.94363 -0.77936 0.076459 0.65332 0.14707 25 -0.35974 0.96189 -0.84889 -0.16487 0.82404 -0.35693 26 -0.36151 0.96315 -0.85371 -0.0040409 0.71027 -0.0080982 27 -0.33164 0.94202 -0.77327 -0.27092 0.89906 -0.61523 28 -0.28252 0.90726 -0.64485 -0.068514 0.75588 -0.14172 29 -0.24504 0.88075 -0.55012 -0.38443 0.97936 -0.91664 30 -0.20277 0.85085 -0.44666 -0.12519 0.79597 -0.26606