3 variables 90 observations for check of v[ 0][ 0] = -0.3393 for check of v[ 0][ 1] = -0.8018 for check of v[ 0][ 2] = -0.4090 for check of v[ 0][ 3] = -0.2733 for check of v[ 1][ 0] = -0.2304 for check of v[ 1][ 1] = 0.5777 for check of v[ 1][ 2] = -0.6651 for check of v[ 1][ 3] = -0.4134 for check of v[ 2][ 0] = -0.4400 for check of v[ 2][ 1] = 0.0613 for check of v[ 2][ 2] = -0.3156 for check of v[ 2][ 3] = 0.8385 for check of v[ 3][ 0] = -0.7989 for check of v[ 3][ 1] = 0.1402 for check of v[ 3][ 2] = 0.5393 for check of v[ 3][ 3] = -0.2265 for i= 0 and j= 0 check summation of Vki*Vkj = 1.0000 for i= 0 and j= 1 check summation of Vki*Vkj = 0.0000 for i= 0 and j= 2 check summation of Vki*Vkj = -0.0000 for i= 0 and j= 3 check summation of Vki*Vkj = -0.0000 for i= 1 and j= 0 check summation of Vki*Vkj = 0.0000 for i= 1 and j= 1 check summation of Vki*Vkj = 1.0000 for i= 1 and j= 2 check summation of Vki*Vkj = 0.0000 for i= 1 and j= 3 check summation of Vki*Vkj = 0.0000 for i= 2 and j= 0 check summation of Vki*Vkj = -0.0000 for i= 2 and j= 1 check summation of Vki*Vkj = 0.0000 for i= 2 and j= 2 check summation of Vki*Vkj = 1.0000 for i= 2 and j= 3 check summation of Vki*Vkj = 0.0000 for i= 3 and j= 0 check summation of Vki*Vkj = -0.0000 for i= 3 and j= 1 check summation of Vki*Vkj = 0.0000 for i= 3 and j= 2 check summation of Vki*Vkj = 0.0000 for i= 3 and j= 3 check summation of Vki*Vkj = 1.0000 w[ 0] = 11.8506 sigma[0] **2 = 50.8461 w[ 1] = 0.1127 sigma[1] **2 = 26.8631 w[ 2] = 1.0520 sigma[2] **2 = 1.1917 w[ 3] = 0.9350 sigma[3] **2 = 1.8725 epsilon/y for data i = 0 is = -0.0055 epsilon/y for data i = 1 is = 0.0764 epsilon/y for data i = 2 is = -1.0981 epsilon/y for data i = 3 is = -0.7320 epsilon/y for data i = 4 is = 0.3257 epsilon/y for data i = 5 is = -0.2481 epsilon/y for data i = 6 is = -0.1227 epsilon/y for data i = 7 is = -0.0557 epsilon/y for data i = 8 is = -0.0557 epsilon/y for data i = 9 is = 0.0127 epsilon/y for data i = 10 is = 0.3151 epsilon/y for data i = 11 is = -0.0160 epsilon/y for data i = 12 is = -0.0217 epsilon/y for data i = 13 is = 0.0631 epsilon/y for data i = 14 is = 0.1012 epsilon/y for data i = 15 is = -0.1878 epsilon/y for data i = 16 is = -0.0438 epsilon/y for data i = 17 is = 0.2753 epsilon/y for data i = 18 is = -0.0122 epsilon/y for data i = 19 is = -0.0398 epsilon/y for data i = 20 is = 0.1543 epsilon/y for data i = 21 is = 0.3099 epsilon/y for data i = 22 is = 0.1990 epsilon/y for data i = 23 is = -0.0486 epsilon/y for data i = 24 is = -0.1534 epsilon/y for data i = 25 is = 0.0881 epsilon/y for data i = 26 is = 0.2887 epsilon/y for data i = 27 is = 0.0950 epsilon/y for data i = 28 is = -0.1067 epsilon/y for data i = 29 is = -0.0608 epsilon/y for data i = 30 is = -0.0567 epsilon/y for data i = 31 is = -0.4140 epsilon/y for data i = 32 is = 0.0766 epsilon/y for data i = 33 is = -0.0008 epsilon/y for data i = 34 is = -0.3356 epsilon/y for data i = 35 is = -0.4123 epsilon/y for data i = 36 is = 0.0028 epsilon/y for data i = 37 is = 0.0106 epsilon/y for data i = 38 is = 0.2451 epsilon/y for data i = 39 is = 0.1125 epsilon/y for data i = 40 is = -0.0816 epsilon/y for data i = 41 is = 0.0521 epsilon/y for data i = 42 is = 0.0675 epsilon/y for data i = 43 is = 0.1707 epsilon/y for data i = 44 is = -0.4016 epsilon/y for data i = 45 is = -3.2838 epsilon/y for data i = 46 is = 0.0676 epsilon/y for data i = 47 is = -0.0125 epsilon/y for data i = 48 is = 0.0652 epsilon/y for data i = 49 is = -0.0792 epsilon/y for data i = 50 is = -0.0513 epsilon/y for data i = 51 is = -0.0044 epsilon/y for data i = 52 is = 0.0490 epsilon/y for data i = 53 is = -0.0129 epsilon/y for data i = 54 is = 0.0166 epsilon/y for data i = 55 is = 0.0283 epsilon/y for data i = 56 is = 0.0510 epsilon/y for data i = 57 is = -0.0180 epsilon/y for data i = 58 is = -0.0368 epsilon/y for data i = 59 is = -0.0678 epsilon/y for data i = 60 is = 0.0040 epsilon/y for data i = 61 is = -0.6374 epsilon/y for data i = 62 is = 0.0362 epsilon/y for data i = 63 is = 0.0620 epsilon/y for data i = 64 is = 0.0634 epsilon/y for data i = 65 is = -0.0834 epsilon/y for data i = 66 is = 0.3538 epsilon/y for data i = 67 is = -0.0601 epsilon/y for data i = 68 is = 0.0437 epsilon/y for data i = 69 is = 0.0051 epsilon/y for data i = 70 is = -0.0379 epsilon/y for data i = 71 is = 0.0438 epsilon/y for data i = 72 is = -0.0206 epsilon/y for data i = 73 is = -0.0290 epsilon/y for data i = 74 is = -0.0202 epsilon/y for data i = 75 is = -0.0717 epsilon/y for data i = 76 is = -0.0240 epsilon/y for data i = 77 is = -0.0294 epsilon/y for data i = 78 is = 0.0467 epsilon/y for data i = 79 is = 0.0051 epsilon/y for data i = 80 is = -0.3516 epsilon/y for data i = 81 is = 0.0291 epsilon/y for data i = 82 is = -0.0332 epsilon/y for data i = 83 is = 0.0211 epsilon/y for data i = 84 is = -0.0063 epsilon/y for data i = 85 is = 0.1461 epsilon/y for data i = 86 is = -0.0480 epsilon/y for data i = 87 is = 0.1189 epsilon/y for data i = 88 is = -0.0117 epsilon/y for data i = 89 is = -1.0531 SSresid = 1.2289 standard residiance = 0.1168540449 mean y = 0.8082 SSto = 6.5147 standard variance of y = 0.2690 F = 129.0328 standard deviation = 0.1195 R ** 2 = 0.8114 adjusted R ** 2 = 0.8114 ------------------------------------------ a[0]=2.67984 a[1]=-4.44055 a[2]=0.26174 a[3]=0.797661 a[4] has w == 0 r = 0.900755; r^2 = 0.81136; t = 19.455