Dati(1,1).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: 16.6667% fit rms cod 1 0.92459 0.066186 0.99431 2 0.85147 0.13037 0.97794 3 0.78899 0.18521 0.95548 4 0.72916 0.23772 0.92665 5 0.66161 0.29701 0.88549 6 0.59246 0.3577 0.83391 7 0.5254 0.41657 0.77476 8 0.4609 0.47318 0.70937 9 0.39191 0.53374 0.63023 10 0.32209 0.59502 0.54044 11 0.25842 0.6509 0.45006 12 0.20021 0.70199 0.36034 13 0.14341 0.75185 0.26625 14 0.087081 0.80129 0.16658 15 0.036188 0.84596 0.071067 16 -0.0086068 0.88528 -0.017288 17 -0.051453 0.92289 -0.10555 18 -0.09239 0.95882 -0.19331 19 -0.12958 0.99146 -0.27596 20 -0.16168 1.0196 -0.34951 21 -0.19203 1.0463 -0.42094 22 -0.22048 1.0712 -0.48957 23 -0.24615 1.0938 -0.55288 24 -0.26819 1.1131 -0.60829 25 -0.28849 1.1309 -0.66021 26 -0.30608 1.1464 -0.70585 27 -0.32013 1.1587 -0.74273 28 -0.33077 1.168 -0.77094 29 -0.33971 1.1759 -0.79481 30 -0.34699 1.1823 -0.81437 Spar_sim -0.68834 1.4819 -1.8505 Dati(1,2).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: 25% fit rms cod 1 0.92704 0.06316 0.99468 2 0.8971 0.089081 0.98941 3 0.88174 0.10237 0.98602 4 0.86996 0.11258 0.98309 5 0.86091 0.12041 0.98065 6 0.85534 0.12523 0.97907 7 0.85329 0.127 0.97848 8 0.85221 0.12794 0.97816 9 0.85099 0.12899 0.9778 10 0.85049 0.12943 0.97765 11 0.85062 0.12932 0.97768 12 0.85121 0.1288 0.97786 13 0.85159 0.12847 0.97797 14 0.85132 0.12871 0.97789 15 0.85017 0.12971 0.97755 16 0.84856 0.1311 0.97706 17 0.84644 0.13293 0.97642 18 0.84469 0.13445 0.97588 19 0.84324 0.1357 0.97543 20 0.84188 0.13688 0.975 21 0.84123 0.13745 0.97479 22 0.84021 0.13833 0.97447 23 0.83928 0.13913 0.97417 24 0.83856 0.13976 0.97394 25 0.83753 0.14065 0.9736 26 0.83702 0.14109 0.97344 27 0.83654 0.1415 0.97328 28 0.8361 0.14188 0.97314 29 0.83548 0.14242 0.97293 30 0.83515 0.1427 0.97283 Spar_sim 0.82549 0.15107 0.96955 Dati(1,3).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: 33.3333% fit rms cod 1 0.95912 0.036798 0.99833 2 0.93969 0.054281 0.99636 3 0.92868 0.064197 0.99491 4 0.91923 0.072698 0.99348 5 0.90985 0.081144 0.99187 6 0.90332 0.087014 0.99065 7 0.89795 0.091852 0.98959 8 0.89428 0.095151 0.98882 9 0.89089 0.098206 0.98809 10 0.88879 0.1001 0.98763 11 0.88687 0.10182 0.9872 12 0.88523 0.1033 0.98683 13 0.8835 0.10486 0.98643 14 0.88232 0.10592 0.98615 15 0.88161 0.10656 0.98598 16 0.88116 0.10696 0.98588 17 0.88053 0.10753 0.98573 18 0.87995 0.10805 0.98559 19 0.87937 0.10857 0.98545 20 0.87902 0.10889 0.98536 21 0.87886 0.10903 0.98533 22 0.87881 0.10908 0.98531 23 0.87866 0.10922 0.98528 24 0.87857 0.1093 0.98525 25 0.87853 0.10933 0.98525 26 0.87853 0.10933 0.98525 27 0.87855 0.10931 0.98525 28 0.87859 0.10928 0.98526 29 0.87864 0.10923 0.98527 30 0.87867 0.1092 0.98528 Spar_sim 0.87206 0.11515 0.98363 Dati(1,4).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: 41.6667% fit rms cod 1 0.95011 0.043962 0.99751 2 0.93915 0.05362 0.9963 3 0.93413 0.05805 0.99566 4 0.92963 0.062017 0.99505 5 0.92651 0.064761 0.9946 6 0.92527 0.065852 0.99442 7 0.92353 0.067391 0.99415 8 0.92081 0.069783 0.99373 9 0.91756 0.072653 0.9932 10 0.91468 0.075188 0.99272 11 0.91177 0.077754 0.99222 12 0.90976 0.079523 0.99186 13 0.90789 0.081175 0.99152 14 0.90596 0.082876 0.99116 15 0.90465 0.084029 0.99091 16 0.9035 0.085037 0.99069 17 0.90104 0.087208 0.99021 18 0.89926 0.088778 0.98985 19 0.89785 0.090024 0.98956 20 0.89698 0.090785 0.98939 21 0.89609 0.091574 0.9892 22 0.89545 0.092137 0.98907 23 0.89499 0.092538 0.98897 24 0.89431 0.09314 0.98883 25 0.89357 0.09379 0.98867 26 0.89307 0.094237 0.98857 27 0.89287 0.094407 0.98852 28 0.89277 0.0945 0.9885 29 0.89262 0.094626 0.98847 30 0.89252 0.094719 0.98845 Spar_sim 0.88329 0.10286 0.98638 Dati(1,5).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: 0% fit rms cod 1 0.95121 0.050032 0.99762 2 0.93084 0.070921 0.99522 3 0.91359 0.088603 0.99253 4 0.89636 0.10627 0.98926 5 0.87614 0.12701 0.98466 6 0.85829 0.14531 0.97992 7 0.84271 0.16129 0.97526 8 0.82939 0.17494 0.97089 9 0.81554 0.18915 0.96597 10 0.80371 0.20128 0.96147 11 0.79319 0.21207 0.95723 12 0.78258 0.22295 0.95273 13 0.77036 0.23548 0.94727 14 0.75748 0.24868 0.94119 15 0.7437 0.26281 0.93431 16 0.73113 0.27571 0.92771 17 0.71595 0.29126 0.91932 18 0.70056 0.30705 0.91034 19 0.68498 0.32303 0.90076 20 0.66968 0.33871 0.89089 21 0.65293 0.35589 0.87954 22 0.63631 0.37293 0.86773 23 0.6195 0.39017 0.85522 24 0.6041 0.40596 0.84326 25 0.58829 0.42218 0.83049 26 0.57225 0.43862 0.81703 27 0.5573 0.45395 0.80402 28 0.54344 0.46816 0.79155 29 0.52804 0.48395 0.77726 30 0.51316 0.49921 0.76299 Spar_sim -0.1222 1.1507 -0.25934 Dati(1,6).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: 25% fit rms cod 1 0.92884 0.062072 0.99494 2 0.87741 0.10693 0.98497 3 0.84542 0.13483 0.9761 4 0.81929 0.15762 0.96734 5 0.7924 0.18108 0.9569 6 0.77223 0.19867 0.94812 7 0.75746 0.21155 0.94118 8 0.74722 0.22048 0.9361 9 0.73859 0.22801 0.93166 10 0.73239 0.23342 0.92838 11 0.72708 0.23805 0.92552 12 0.72364 0.24106 0.92362 13 0.71999 0.24423 0.9216 14 0.71694 0.2469 0.91988 15 0.71383 0.24961 0.91811 16 0.71093 0.25214 0.91644 17 0.70753 0.25511 0.91446 18 0.70433 0.25789 0.91258 19 0.70085 0.26093 0.91051 20 0.6979 0.2635 0.90874 21 0.69428 0.26666 0.90654 22 0.69052 0.26994 0.90422 23 0.68704 0.27298 0.90205 24 0.68433 0.27534 0.90035 25 0.68141 0.27788 0.8985 26 0.67882 0.28014 0.89685 27 0.67632 0.28233 0.89523 28 0.67456 0.28386 0.89409 29 0.67283 0.28537 0.89296 30 0.67146 0.28657 0.89206 Spar_sim 0.63333 0.31982 0.86555 Dati(1,7).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: NaN% fit rms cod 1 NaN NaN NaN 2 NaN NaN NaN 3 NaN NaN NaN 4 NaN NaN NaN 5 NaN NaN NaN 6 NaN NaN NaN 7 NaN NaN NaN 8 NaN NaN NaN 9 NaN NaN NaN 10 NaN NaN NaN 11 NaN NaN NaN 12 NaN NaN NaN 13 NaN NaN NaN 14 NaN NaN NaN 15 NaN NaN NaN 16 NaN NaN NaN 17 NaN NaN NaN 18 NaN NaN NaN 19 NaN NaN NaN 20 NaN NaN NaN 21 NaN NaN NaN 22 NaN NaN NaN 23 NaN NaN NaN 24 NaN NaN NaN 25 NaN NaN NaN 26 NaN NaN NaN 27 NaN NaN NaN 28 NaN NaN NaN 29 NaN NaN NaN 30 NaN NaN NaN Spar_sim NaN NaN NaN Dati(1,8).t.sseh_norm(p,n).Mnpf n=500 p=25 Sparsit�: 50% fit rms cod 1 0.9393 0.065534 0.99632 2 0.8975 0.11067 0.98949 3 0.86095 0.15013 0.98067 4 0.82962 0.18396 0.97097 5 0.80388 0.21175 0.96154 6 0.78504 0.2321 0.95379 7 0.77043 0.24787 0.9473 8 0.759 0.26021 0.94192 9 0.74984 0.2701 0.93742 10 0.74348 0.27697 0.9342 11 0.73886 0.28196 0.9318 12 0.73548 0.28561 0.93003 13 0.73501 0.28611 0.92978 14 0.73443 0.28674 0.92947 15 0.73344 0.28781 0.92895 16 0.73269 0.28862 0.92854 17 0.73135 0.29006 0.92783 18 0.72959 0.29197 0.92688 19 0.72827 0.2934 0.92616 20 0.72721 0.29453 0.92559 21 0.72606 0.29578 0.92495 22 0.72536 0.29653 0.92458 23 0.72484 0.2971 0.92428 24 0.72416 0.29782 0.92391 25 0.72343 0.29861 0.92351 26 0.72302 0.29905 0.92328 27 0.72294 0.29914 0.92324 28 0.72277 0.29933 0.92315 29 0.72262 0.29949 0.92306 30 0.72235 0.29978 0.92291 Spar_sim 0.68918 0.3356 0.90339