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Data X:
LTG µg/mL/dosis Sexo 1=hombre. 2=mujer Edad Dosis Dosis/Kg LTG µg/mL LTG µg/mL/dosis/Kg LTG µg/mL/dosis LTG µg/mL/dosis Log10 GRUPO DE TRATAMIENTO UGT1A4_0=wt. 1=Ht. 2=Hm UGT1A4*1b_0=wt. 1=Ht. 2=1b UGT1A4*1c_0=wt. 1=Ht. 2=Hm UGT1A4*2_0=wt. 1=Ht. 2=Hm UGT1A4*3a_0=wt. 1=Ht. 2=Hm UGT1A4*3b_0=wt. 1=Ht. 2=Hm UGT1A4*7_0=wt. 1=Ht. 2=Hm UGT1A4_204 G>A_ 0=wt. 1=Ht. 2= UGT1A4_384 T>C_0=wt. 1=Ht. 2=H UGT1A4_424 A>C_0=wt. 1=Ht. 2=H UGT1A4_496C>T _0=wt. 1=Ht. 2=H UGT1A4_526 A>T_0=wt. 1=Ht. 2=H UGT1A1*6_ 0=wt. 1=Ht. 2=Hm UGT1A1*7_0=wt. 1=Ht. 2=Hm UGT1A1*29_0=wt. 1=Ht. 2=Hm UGT1A1*28 0=wt. 1=Ht. 2=Hm UGT1A1*37 0=wt. 1=Ht UGT1A1*28 0=wt. 1 UGT2B7 372 A>G_0=wt. 1=Ht. 2=H UGT2B7 161 C>T_ 0=wt. 1=Ht. 2= UGT2B7 801 A>T 802 T>C_0=AT/AT ABCB1 1236 T>C_0=wt. 1=Ht. 2=H ABCB1 3435 T>C_0=wt. 1=Ht. 2=H ABCB1 2677 C/AT_ 0=wt. 1=Ht(CA Haplotipo ABCB1 LTG 01 0.0110 2.0000 29.0000 300.0000 5.88 3.30 0.56 0.0110 -1.9600 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 1. 2. LTG 02 0.0170 1.0000 18.0000 400.0000 4.12 6.80 1.65 0.0170 -1.7700 2.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 0. 0. 0. 1. LTG 03 0.0580 2.0000 23.0000 200.0000 3.85 11.60 3.02 0.0580 -1.2400 2.0000 1.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 1. 1. 0. 1. 0. 0. 0. 0. 0. 2. 2. 0. 0. 0. 1. LTG 04 0.0040 1.0000 32.0000 200.0000 2.33 0.80 0.34 0.0040 -2.4000 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 0. 2. 2. 1. 1. 3. LTG 05 0.0105 1.0000 24.0000 200.0000 2.33 2.10 0.90 0.0105 -1.9800 3.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 0. 0. 0. 1. LTG 06 0.0405 1.0000 26.0000 200.0000 3.33 8.10 2.43 0.0405 -1.3900 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 0. 0. 0. 1. LTG 07 0.0405 1.0000 24.0000 200.0000 2.56 8.10 3.16 0.0405 -1.3900 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 0. 0. 2. 2. LTG 08 0.0170 2.0000 18.0000 200.0000 3.70 3.40 0.92 0.0170 -1.7700 0.0000 1.00 0.0000 0.0000 1.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 1. 2. LTG 09 0.0233 2.0000 32.0000 400.0000 7.02 9.30 1.33 0.0233 -1.6300 0.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 2. LTG 10 0.0175 2.0000 21.0000 200.0000 3.72 3.50 0.94 0.0175 -1.7600 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 1. 1. 1. 1. 2. LTG 11 0.0260 2.0000 20.0000 50.0000 0.81 1.30 1.61 0.0260 -1.5900 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 2. 2. 3. 3. LTG 12 0.0150 1.0000 72.0000 100.0000 1.30 1.50 1.16 0.0150 -1.8200 0.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 2. 1. 1. 1. 2. LTG 13 0.0045 1.0000 60.0000 200.0000 3.23 0.90 0.28 0.0045 -2.3500 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 2. 3. 3. LTG 14 0.0050 1.0000 27.0000 500.0000 4.10 2.50 0.61 0.0050 -2.3000 2.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 2. 2. 1. 1. 3. LTG 15 0.0545 2.0000 20.0000 200.0000 3.23 10.90 3.38 0.0545 -1.2600 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 0. 0. 1. 3. LTG 16 0.0120 2.0000 24.0000 50.0000 0.98 0.60 0.61 0.0120 -1.9200 3.0000 1.00 0.0000 0.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 2. 2. 3. 3. LTG-100 0.0128 2.0000 34.0000 400.0000 5.33 5.10 0.96 0.0128 -1.8900 3.0000 2.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 1. 1. 4. LTG-101 0.0105 1.0000 13.0000 200.0000 4.08 2.10 0.51 0.0105 -1.9800 3.0000 2.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 1. 1. 0. 2. LTG-102 0.0508 1.0000 30.0000 400.0000 6.35 20.30 3.20 0.0508 -1.2900 2.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 1. 1. 0. 2. LTG-103 0.0377 2.0000 22.0000 300.0000 5.66 11.30 2.00 0.0377 -1.4200 0.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 0. 2. LTG-104 0.0730 1.0000 19.0000 300.0000 3.30 21.90 6.64 0.0730 -1.1400 2.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 2. LTG-107 0.0725 1.0000 27.0000 200.0000 3.85 14.50 3.77 0.0725 -1.1400 1.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 0. 2. 2. LTG-108 0.0073 1.0000 33.0000 600.0000 4.92 4.40 0.89 0.0073 -2.1300 3.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 1. 2. 3. 3. LTG-110 0.0250 2.0000 32.0000 100.0000 1.79 2.50 1.40 0.0250 -1.6000 3.0000 1.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 1. 0. 1. 0. 2. LTG-117 0.0355 2.0000 25.0000 200.0000 3.13 7.10 2.27 0.0355 -1.4500 3.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 1. 1. 1. 1. 1. 2. 2. LTG-118 0.0650 1.0000 23.0000 100.0000 1.23 6.50 5.27 0.0650 -1.1900 1.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 1. 0. 2. 1. 1. 2. 2. LTG-120 0.0775 2.0000 22.0000 200.0000 3.42 15.50 4.53 0.0775 -1.1100 1.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 0. 0. 1. 2. LTG-121 0.0540 2.0000 49.0000 100.0000 0.91 5.40 5.94 0.0540 -1.2700 3.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 1. 1. 1. 0. 2. LTG-122 0.0460 1.0000 24.0000 200.0000 2.97 9.20 3.10 0.0460 -1.3400 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 1. 0. 2. 1. 1. 2. 2. LTG-18 0.0625 1.0000 15.0000 200.0000 2.38 12.50 5.25 0.0625 -1.2000 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 0. 1. 2. LTG-19 0.0180 2.0000 22.0000 100.0000 1.89 1.80 0.95 0.0180 -1.7400 3.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 1. 1. 2. 0. 1. 3. LTG-20 0.0595 2.0000 55.0000 200.0000 3.08 11.90 3.87 0.0595 -1.2300 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 2. 1. 1. 3. LTG-21 0.0320 1.0000 38.0000 300.0000 3.75 9.60 2.56 0.0320 -1.4900 1.0000 2.00 1.0000 0.0000 0.00 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 0. 0. 2. 2. LTG-22 0.0743 1.0000 21.0000 300.0000 5.13 22.30 4.35 0.0743 -1.1300 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 2. 1. 1. 1. 2. LTG-24 0.0060 2.0000 30.0000 200.0000 4.40 1.20 0.27 0.0060 -2.2200 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 2. 1. 1. 3. LTG-25 0.0765 2.0000 39.0000 200.0000 3.51 15.30 4.36 0.0765 -1.1200 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 2. 2. 3. 3. LTG-26 0.0853 2.0000 18.0000 150.0000 2.68 12.80 4.78 0.0853 -1.0700 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 2. 2. 3. 3. LTG-27 0.0510 2.0000 19.0000 100.0000 1.20 5.10 4.23 0.0510 -1.2900 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 1. 2. LTG-28 0.0388 1.0000 30.0000 400.0000 6.37 15.50 2.43 0.0388 -1.4100 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 2. LTG-29 0.1120 2.0000 46.0000 100.0000 1.64 11.20 6.83 0.1120 -0.9500 3.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 1. 2. LTG-31 0.0543 1.0000 25.0000 300.0000 4.17 16.30 3.91 0.0543 -1.2600 1.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 0. 0. 0. 0. 1. 1. 2. 1. 1. 3. LTG-32 0.0473 2.0000 16.0000 400.0000 7.84 18.90 2.41 0.0473 -1.3300 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 0. 0. 2. LTG-33 0.0143 1.0000 67.0000 300.0000 3.75 4.30 1.15 0.0143 -1.8400 3.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 2. 0. 1. 1. 0. 2. LTG-34 0.0480 1.0000 38.0000 100.0000 1.32 4.80 3.65 0.0480 -1.3200 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 0. 2. 0. 1. 2. 2. LTG-35 0.0368 1.0000 47.0000 400.0000 5.48 14.70 2.68 0.0368 -1.4300 2.0000 1.00 0.0000 0.0000 0.00 1. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 1. 0. 2. 1. 0. 1. 2. LTG-36 0.0255 2.0000 27.0000 200.0000 3.70 5.10 1.38 0.0255 -1.5900 2.0000 2.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 1. 1. 2. 2. 3. 3. LTG-37 0.0345 2.0000 73.0000 200.0000 3.92 6.90 1.76 0.0345 -1.4600 1.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 1. 0. 2. 1. 1. 1. 2. LTG-38 0.0100 2.0000 17.0000 200.0000 2.63 2.00 0.76 0.0100 -2.0000 3.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 2. 2. LTG-39 0.0530 1.0000 23.0000 100.0000 2.00 5.30 2.65 0.0530 -1.2800 2.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 1. 3. 0. 0. 2. 0. 0. 0. 1. LTG-40 0.0373 1.0000 37.0000 300.0000 6.28 11.20 1.78 0.0373 -1.4300 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 0. 2. LTG-42 0.0465 2.0000 35.0000 200.0000 2.94 9.30 3.16 0.0465 -1.3300 1.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 1. 1. 2. LTG-43 0.0850 2.0000 19.0000 100.0000 2.11 8.50 4.02 0.0850 -1.0700 1.0000 2.00 0.0000 0.0000 0.00 0. 2. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 2. 1. 1. 3. LTG-44 0.0123 1.0000 40.0000 300.0000 4.00 3.70 0.93 0.0123 -1.9100 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 1. 0. 1. 2. LTG-45 0.0153 2.0000 44.0000 400.0000 5.26 6.10 1.16 0.0153 -1.8200 3.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 2. LTG-46 0.0135 2.0000 24.0000 200.0000 3.85 2.70 0.70 0.0135 -1.8700 3.0000 1.00 0.0000 0.0000 0.00 1. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 0. 0. 3. 3. LTG-47 0.0090 2.0000 36.0000 300.0000 5.45 2.70 0.50 0.0090 -2.0500 3.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 2. 1. 3. LTG-48 0.0490 2.0000 32.0000 100.0000 1.22 4.90 4.02 0.0490 -1.3100 2.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 1. 1. 0. 0. 0. 0. 0. 1. 1. 1. 0. 1. 2. LTG-49 0.0457 1.0000 26.0000 300.0000 4.62 13.70 2.97 0.0457 -1.3400 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 0. 1. 1. 2. LTG-50 0.0700 2.0000 33.0000 50.0000 0.68 3.50 5.11 0.0700 -1.1500 1.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 1. 3. 1. 1. 1. 2. 2. 0. 3. LTG-51 0.0455 1.0000 20.0000 200.0000 2.50 9.10 3.64 0.0455 -1.3400 1.0000 2.00 1.0000 0.0000 1.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 1. 3. 0. 0. 2. 2. 2. 2. 3. LTG-52 0.0343 2.0000 39.0000 300.0000 4.23 10.30 2.44 0.0343 -1.4600 1.0000 1.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 1. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 2. 0. 0. 3. LTG-53 0.0163 2.0000 43.0000 300.0000 4.92 4.90 1.00 0.0163 -1.7900 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 1. 3. 0. 1. 1. 1. 1. 1. 2. LTG-54 0.0330 1.0000 48.0000 200.0000 2.99 6.60 2.21 0.0330 -1.4800 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 0. 2. 0. 1. 3. 3. LTG-58 0.0113 1.0000 30.0000 300.0000 5.17 3.40 0.66 0.0113 -1.9500 0.0000 2.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 2. 2. 0. 3. LTG-59 0.0233 2.0000 30.0000 300.0000 4.26 7.00 1.65 0.0233 -1.6300 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 2. LTG-61 0.0073 1.0000 29.0000 300.0000 3.66 2.20 0.60 0.0073 -2.1300 0.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 1. 1. 2. LTG-62 0.0095 2.0000 14.0000 400.0000 6.78 3.80 0.56 0.0095 -2.0200 0.0000 2.00 0.0000 1.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 2. 0. 0. 3. 3. LTG-63 0.0280 2.0000 39.0000 50.0000 0.85 1.40 1.65 0.0280 -1.5500 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 0. 1. 1. 2. LTG-64 0.0275 2.0000 67.0000 200.0000 2.67 5.50 2.06 0.0275 -1.5600 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 3. 3. LTG-68 0.0180 1.0000 42.0000 200.0000 2.20 3.60 1.64 0.0180 -1.7400 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 1. 2. LTG-69 0.0155 1.0000 17.0000 400.0000 5.06 6.20 1.22 0.0155 -1.8100 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 2. 1. 1. 1. 2. LTG-70 0.0105 1.0000 23.0000 200.0000 2.02 2.10 1.04 0.0105 -1.9800 3.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 2. LTG-71 0.0370 1.0000 23.0000 300.0000 3.75 11.10 2.96 0.0370 -1.4300 2.0000 1.00 0.0000 0.0000 0.00 0. 1. 0. 0. 0. 0. 0. 0. 1. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 1. 2. LTG-72 0.0420 1.0000 27.0000 100.0000 1.20 4.20 3.49 0.0420 -1.3800 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 2. 2. 0. 3. LTG-73 0.0567 2.0000 22.0000 300.0000 4.84 17.00 3.51 0.0567 -1.2500 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 1. 0. 2. 0. 0. 3. 3. LTG-74 0.0113 1.0000 31.0000 300.0000 4.71 3.40 0.72 0.0113 -1.9500 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 1. 2. 2. 0. 3. LTG-75 0.0360 2.0000 52.0000 100.0000 1.39 3.60 2.59 0.0360 -1.4400 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 0. 2. 0. 1. 1. 2. LTG-76 0.0193 1.0000 64.0000 150.0000 2.59 2.90 1.12 0.0193 -1.7100 0.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 1. 2. 1. 1. 1. 2. LTG-77 0.0057 1.0000 27.0000 300.0000 5.36 1.70 0.32 0.0057 -2.2500 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 0. 1. 2. LTG-78 0.0085 1.0000 39.0000 200.0000 2.20 1.70 0.77 0.0085 -2.0700 3.0000 2.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 2. 2. 0. 3. LTG-79 0.0080 1.0000 40.0000 200.0000 2.63 1.60 0.61 0.0080 -2.1000 0.0000 1.00 1.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 0. 2. 0. 3. LTG-83 0.0577 1.0000 23.0000 300.0000 5.17 17.30 3.34 0.0577 -1.2400 1.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 1. 1. 1. 1. 1. 1. 2. LTG-84 0.0298 1.0000 23.0000 400.0000 8.70 11.90 1.37 0.0298 -1.5300 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 1. 0. 1. 0. 1. 2. LTG-85 0.0335 2.0000 26.0000 400.0000 5.00 13.40 2.68 0.0335 -1.4700 1.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 1. 0. 2. 1. 1. 3. 3. LTG-86 0.0293 1.0000 38.0000 300.0000 3.85 8.80 2.29 0.0293 -1.5300 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 0. 1. 3. 3. LTG-87 0.0200 2.0000 38.0000 200.0000 2.98 4.00 1.34 0.0200 -1.7000 3.0000 2.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 0. 3. 3. LTG-88 0.0560 1.0000 28.0000 100.0000 1.45 5.60 3.86 0.0560 -1.2500 2.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 0. 1. 2. LTG-89 0.0180 2.0000 65.0000 200.0000 2.98 3.60 1.21 0.0180 -1.7400 2.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 1. 1. 1. 1. 1. 2. LTG-90 0.0650 2.0000 23.0000 200.0000 2.60 13.00 5.01 0.0650 -1.1900 0.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 1. 1. 1. 1. 1. 2. LTG-91 0.0185 2.0000 30.0000 200.0000 3.45 3.70 1.07 0.0185 -1.7300 3.0000 0.00 0.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 0. 2. 2. 2. 0. 3. LTG-92 0.0357 1.0000 16.0000 300.0000 4.48 10.70 2.39 0.0357 -1.4500 0.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 0. 0. 0. 0. 0. 0. 2. 2. 1. 0. 3. LTG-93 0.0612 2.0000 20.0000 250.0000 3.72 15.30 4.11 0.0612 -1.2100 2.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 1. 1. 2. LTG-94 0.0380 1.0000 19.0000 50.0000 0.62 1.90 3.08 0.0380 -1.4200 1.0000 2.00 1.0000 0.0000 0.00 0. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 0. 1. 2. LTG-95 0.0185 2.0000 30.0000 400.0000 6.90 7.40 1.07 0.0185 -1.7300 3.0000 2.00 1.0000 1.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 0. 1. 1. 1. 1. 1. 1. 2. LTG-96 0.0085 2.0000 44.0000 400.0000 6.90 3.40 0.49 0.0085 -2.0700 3.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 2. 0. 1. 0. 1. 1. 1. 2. 1. 3. LTG-97 0.0135 2.0000 19.0000 200.0000 2.86 2.70 0.95 0.0135 -1.8700 0.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 1. 1. 1. 2. LTG-98 0.2480 2.0000 33.0000 50.0000 1.14 12.40 10.91 0.2480 -0.6100 1.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 2. 0. 1. 1. 2. LTG-99 0.0545 1.0000 32.0000 200.0000 4.17 10.90 2.62 0.0545 -1.2600 2.0000 2.00 2.0000 0.0000 0.00 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 1. 0. 2. 0. 0. 2. 1. 1. 1. 2.
Names of X columns:
µg/mL/dosis
Sample Range:
(leave blank to include all observations)
From:
To:
Column Number of Endogenous Series
(?)
Fixed Seasonal Effects
Do not include Seasonal Dummies
Do not include Seasonal Dummies
Include Seasonal Dummies
Type of Equation
Linear Trend
No Linear Trend
Linear Trend
First Differences
Seasonal Differences (s)
First and Seasonal Differences (s)
Degree of Predetermination (lagged endogenous variables)
Degree of Seasonal Predetermination
Seasonality
12
12
1
2
3
4
5
6
7
8
9
10
11
12
Chart options
R Code
par6 <- '12' par5 <- '0' par4 <- '0' par3 <- 'No Linear Trend' par2 <- 'Do not include Seasonal Dummies' par1 <- '1' library(lattice) library(lmtest) library(car) library(MASS) n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test mywarning <- '' par6 <- as.numeric(par6) if(is.na(par6)) { par6 <- 12 mywarning = 'Warning: you did not specify the seasonality. The seasonal period was set to s = 12.' } par1 <- as.numeric(par1) if(is.na(par1)) { par1 <- 1 mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.' } if (par4=='') par4 <- 0 par4 <- as.numeric(par4) if (!is.numeric(par4)) par4 <- 0 if (par5=='') par5 <- 0 par5 <- as.numeric(par5) if (!is.numeric(par5)) par5 <- 0 x <- na.omit(t(y)) k <- length(x[1,]) n <- length(x[,1]) x1 <- cbind(x[,par1], x[,1:k!=par1]) mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) colnames(x1) <- mycolnames #colnames(x)[par1] x <- x1 if (par3 == 'First Differences'){ (n <- n -1) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+1,j] - x[i,j] } } x <- x2 } if (par3 == 'Seasonal Differences (s)'){ (n <- n - par6) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+par6,j] - x[i,j] } } x <- x2 } if (par3 == 'First and Seasonal Differences (s)'){ (n <- n -1) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+1,j] - x[i,j] } } x <- x2 (n <- n - par6) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+par6,j] - x[i,j] } } x <- x2 } if(par4 > 0) { x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep=''))) for (i in 1:(n-par4)) { for (j in 1:par4) { x2[i,j] <- x[i+par4-j,par1] } } x <- cbind(x[(par4+1):n,], x2) n <- n - par4 } if(par5 > 0) { x2 <- array(0, dim=c(n-par5*par6,par5), dimnames=list(1:(n-par5*par6), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep=''))) for (i in 1:(n-par5*par6)) { for (j in 1:par5) { x2[i,j] <- x[i+par5*par6-j*par6,par1] } } x <- cbind(x[(par5*par6+1):n,], x2) n <- n - par5*par6 } if (par2 == 'Include Seasonal Dummies'){ x2 <- array(0, dim=c(n,par6-1), dimnames=list(1:n, paste('M', seq(1:(par6-1)), sep =''))) for (i in 1:(par6-1)){ x2[seq(i,n,par6),i] <- 1 } x <- cbind(x, x2) } if (par2 == 'Include Monthly Dummies'){ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) for (i in 1:11){ x2[seq(i,n,12),i] <- 1 } x <- cbind(x, x2) } if (par2 == 'Include Quarterly Dummies'){ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) for (i in 1:3){ x2[seq(i,n,4),i] <- 1 } x <- cbind(x, x2) } (k <- length(x[n,])) if (par3 == 'Linear Trend'){ x <- cbind(x, c(1:n)) colnames(x)[k+1] <- 't' } print(x) (k <- length(x[n,])) head(x) df <- as.data.frame(x) (mylm <- lm(df)) (mysum <- summary(mylm)) if (n > n25) { kp3 <- k + 3 nmkm3 <- n - k - 3 gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) numgqtests <- 0 numsignificant1 <- 0 numsignificant5 <- 0 numsignificant10 <- 0 for (mypoint in kp3:nmkm3) { j <- 0 numgqtests <- numgqtests + 1 for (myalt in c('greater', 'two.sided', 'less')) { j <- j + 1 gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value } if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 } gqarr } bitmap(file='test0.png') plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') points(x[,1]-mysum$resid) grid() dev.off() bitmap(file='test1.png') plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() bitmap(file='test2.png') sresid <- studres(mylm) hist(sresid, freq=FALSE, main='Distribution of Studentized Residuals') xfit<-seq(min(sresid),max(sresid),length=40) yfit<-dnorm(xfit) lines(xfit, yfit) grid() dev.off() bitmap(file='test3.png') densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() bitmap(file='test4.png') qqPlot(mylm, main='QQ Plot') grid() dev.off() (myerror <- as.ts(mysum$resid)) bitmap(file='test5.png') dum <- cbind(lag(myerror,k=1),myerror) dum dum1 <- dum[2:length(myerror),] dum1 z <- as.data.frame(dum1) print(z) plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') lines(lowess(z)) abline(lm(z)) grid() dev.off() bitmap(file='test6.png') acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') grid() dev.off() bitmap(file='test7.png') pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') grid() dev.off() bitmap(file='test8.png') opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) plot(mylm, las = 1, sub='Residual Diagnostics') par(opar) dev.off() if (n > n25) { bitmap(file='test9.png') plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') grid() dev.off() } load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) a<-table.row.end(a) myeq <- colnames(x)[1] myeq <- paste(myeq, '[t] = ', sep='') for (i in 1:k){ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ') if (rownames(mysum$coefficients)[i] != '(Intercept)') { myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') } } myeq <- paste(myeq, ' + e[t]') a<-table.row.start(a) a<-table.element(a, myeq) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, mywarning) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Multiple Linear Regression - Ordinary Least Squares', 6, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',header=TRUE) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'T-STAT<br />H0: parameter = 0',header=TRUE) a<-table.element(a,'2-tail p-value',header=TRUE) a<-table.element(a,'1-tail p-value',header=TRUE) a<-table.row.end(a) for (i in 1:k){ a<-table.row.start(a) a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+')) a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' ')) a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+')) a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' ')) a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' ')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R',1,TRUE) a<-table.element(a,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'R-squared',1,TRUE) a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Adjusted R-squared',1,TRUE) a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (value)',1,TRUE) a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) a<-table.element(a, signif(mysum$fstatistic[2],6)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) a<-table.element(a, signif(mysum$fstatistic[3],6)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'p-value',1,TRUE) a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residual Standard Deviation',1,TRUE) a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Sum Squared Residuals',1,TRUE) a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' ')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable3.tab') myr <- as.numeric(mysum$resid) myr a <-table.start() a <- table.row.start(a) a <- table.element(a,'Menu of Residual Diagnostics',2,TRUE) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Description',1,TRUE) a <- table.element(a,'Link',1,TRUE) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Histogram',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_histogram.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Central Tendency',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_centraltendency.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'QQ Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_fitdistrnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Kernel Density Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_density.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Skewness/Kurtosis Test',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Skewness-Kurtosis Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis_plot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Harrell-Davis Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_harrell_davis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Bootstrap Plot -- Central Tendency',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Blocked Bootstrap Plot -- Central Tendency',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'(Partial) Autocorrelation Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_autocorrelation.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Spectral Analysis',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_spectrum.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Tukey lambda PPCC Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_tukeylambda.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Box-Cox Normality Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_boxcoxnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Summary Statistics',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_summary1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a<-table.end(a) table.save(a,file='mytable7.tab') if(n < 200) { a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Time or Index', 1, TRUE) a<-table.element(a, 'Actuals', 1, TRUE) a<-table.element(a, 'Interpolation<br />Forecast', 1, TRUE) a<-table.element(a, 'Residuals<br />Prediction Error', 1, TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,i, 1, TRUE) a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' ')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable4.tab') if (n > n25) { a<-table.start() a<-table.row.start(a) a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-values',header=TRUE) a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'breakpoint index',header=TRUE) a<-table.element(a,'greater',header=TRUE) a<-table.element(a,'2-sided',header=TRUE) a<-table.element(a,'less',header=TRUE) a<-table.row.end(a) for (mypoint in kp3:nmkm3) { a<-table.row.start(a) a<-table.element(a,mypoint,header=TRUE) a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' ')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable5.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Description',header=TRUE) a<-table.element(a,'# significant tests',header=TRUE) a<-table.element(a,'% significant tests',header=TRUE) a<-table.element(a,'OK/NOK',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'1% type I error level',header=TRUE) a<-table.element(a,signif(numsignificant1,6)) a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' ')) if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'5% type I error level',header=TRUE) a<-table.element(a,signif(numsignificant5,6)) a<-table.element(a,signif(numsignificant5/numgqtests,6)) if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'10% type I error level',header=TRUE) a<-table.element(a,signif(numsignificant10,6)) a<-table.element(a,signif(numsignificant10/numgqtests,6)) if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable6.tab') } } a<-table.start() a<-table.row.start(a) a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of fitted values',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) reset_test_fitted <- resettest(mylm,power=2:3,type='fitted') a<-table.element(a,paste('<pre>',RC.texteval('reset_test_fitted'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of regressors',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) reset_test_regressors <- resettest(mylm,power=2:3,type='regressor') a<-table.element(a,paste('<pre>',RC.texteval('reset_test_regressors'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of principal components',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) reset_test_principal_components <- resettest(mylm,power=2:3,type='princomp') a<-table.element(a,paste('<pre>',RC.texteval('reset_test_principal_components'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable8.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Variance Inflation Factors (Multicollinearity)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) vif <- vif(mylm) a<-table.element(a,paste('<pre>',RC.texteval('vif'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable9.tab')
Compute
Summary of computational transaction
Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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