Problem Formulation Example-/-["Work in Progress"]
...[***Paper/Reference Source***]...
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Experimental Data set{26}/cis-resveratrol
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0.00E+00,0.00E+00
9.67E-01,4.13E+00
2.30E+00,9.30E+00
3.75E+00,1.50E+01
4.72E+00,1.96E+01
6.05E+00,2.53E+01
7.25E+00,3.05E+01
8.58E+00,3.51E+01
9.79E+00,3.93E+01
1.15E+01,4.34E+01
1.31E+01,4.75E+01
1.44E+01,5.06E+01
1.61E+01,5.58E+01
1.77E+01,5.94E+01
1.97E+01,6.35E+01
2.16E+01,6.61E+01
2.38E+01,6.81E+01
2.56E+01,7.07E+01
2.79E+01,7.38E+01
3.06E+01,7.64E+01
3.34E+01,7.89E+01
3.66E+01,8.15E+01
4.07E+01,8.19E+01
4.39E+01,8.29E+01
4.61E+01,8.34E+01
4.79E+01,8.34E+01
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Experimental Data set{26}/cis-resveratrol P = "not fixed"
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y = Exp(a) * Power((t/48.0),a)*Exp( - a * (t/48.0))*b ................> [ WF = τp·ep(1-τ)]
x1 y yc y-yc SEest YcLo YcHi
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.9670 4.1300 4.6619 -0.5319 0.1225 4.4091 4.9148
2.3000 9.3000 10.6695 -1.3695 0.1953 10.2665 11.0725
3.7500 15.0000 16.7795 -1.7795 0.2343 16.2958 17.2632
4.7200 19.6000 20.6418 -1.0418 0.2476 20.1307 21.1529
6.0500 25.3000 25.6626 -0.3626 0.2552 25.1358 26.1894
7.2500 30.5000 29.9336 0.5664 0.2549 29.4075 30.4597
8.5800 35.1000 34.3948 0.7052 0.2492 33.8804 34.9092
9.7900 39.3000 38.2162 1.0838 0.2410 37.7187 38.7136
11.5000 43.4000 43.2507 0.1493 0.2268 42.7827 43.7188
13.1000 47.5000 47.5940 -0.0940 0.2127 47.1549 48.0330
14.4000 50.6000 50.8751 -0.2751 0.2020 50.4582 51.2921
16.1000 55.8000 54.8484 0.9516 0.1902 54.4558 55.2410
17.7000 59.4000 58.2765 1.1235 0.1823 57.9002 58.6529
19.7000 63.5000 62.1624 1.3376 0.1777 61.7956 62.5291
21.6000 66.1000 65.4685 0.6315 0.1786 65.0998 65.8372
23.8000 68.1000 68.8599 -0.7599 0.1851 68.4779 69.2418
25.6000 70.7000 71.3093 -0.6093 0.1934 70.9102 71.7084
27.9000 73.8000 74.0438 -0.2438 0.2062 73.6183 74.4693
30.6000 76.4000 76.7319 -0.3319 0.2221 76.2735 77.1903
33.4000 78.9000 78.9778 -0.0778 0.2377 78.4871 79.4684
36.6000 81.5000 80.9372 0.5628 0.2529 80.4153 81.4592
40.7000 81.9000 82.6134 -0.7134 0.2669 82.0625 83.1642
43.9000 82.9000 83.3523 -0.4523 0.2734 82.7881 83.9165
46.1000 83.4000 83.6049 -0.2049 0.2756 83.0360 84.1737
47.9000 83.4000 83.6711 -0.2711 0.2762 83.1011 84.2412
Corr. Coeff. = 0.999586; r*r = 0.999172
RMS Error = 0.797579; d.f = 24
Parameter Estimates...
p1= 0.987204 +/- 0.009606; p= 0.0000
p2= 83.671313 +/- 0.276206; p= 0.0000
Covariance Matrix Terms and Error-Correlations...
B(1,1)= 0.00009227261557938563; r= 1.0000
B(1,2)=B(2,1)= 0.0015405749964052014; r= 0.5806
B(2,2)= 0.07628966033110268; r= 1.0000
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Experimental Data set{26}/cis-resveratrol P = = 0.81
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y = Exp(a) * Power((t/48.0),a)*Exp( - a * (t/48.0))*b
x1 y yc y-yc SEest YcLo YcHi
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.9670 4.1300 7.7794 -3.6494 0.8311 6.0640 9.4948
2.3000 9.3000 15.2937 -5.9937 1.1339 12.9533 17.6340
3.7500 15.0000 22.1335 -7.1335 1.2488 19.5560 24.7110
4.7200 19.6000 26.2121 -6.6121 1.2687 23.5936 28.8305
6.0500 25.3000 31.3110 -6.0110 1.2548 28.7212 33.9009
7.2500 30.5000 35.5044 -5.0044 1.2178 32.9909 38.0179
8.5800 35.1000 39.7686 -4.6686 1.1620 37.3703 42.1669
9.7900 39.3000 43.3406 -4.0406 1.1050 41.0599 45.6213
11.5000 43.4000 47.9485 -4.5485 1.0239 45.8353 50.0617
13.1000 47.5000 51.8447 -4.3447 0.9552 49.8732 53.8161
14.4000 50.6000 54.7447 -4.1447 0.9087 52.8692 56.6203
16.1000 55.8000 58.2111 -2.4111 0.8643 56.4272 59.9950
17.7000 59.4000 61.1648 -1.7648 0.8414 59.4283 62.9014
19.7000 63.5000 64.4747 -0.9747 0.8379 62.7454 66.2040
21.6000 66.1000 67.2609 -1.1609 0.8565 65.4931 69.0288
23.8000 68.1000 70.0923 -1.9923 0.8973 68.2403 71.9442
25.6000 70.7000 72.1213 -1.4213 0.9399 70.1814 74.0612
27.9000 73.8000 74.3714 -0.5714 0.9995 72.3084 76.4344
30.6000 76.4000 76.5685 -0.1685 1.0693 74.3616 78.7754
33.4000 78.9000 78.3933 0.5067 1.1351 76.0506 80.7360
36.6000 81.5000 79.9777 1.5223 1.1974 77.5063 82.4490
40.7000 81.9000 81.3273 0.5727 1.2540 78.7391 83.9155
43.9000 82.9000 81.9207 0.9793 1.2799 79.2791 84.5623
46.1000 83.4000 82.1233 1.2767 1.2889 79.4632 84.7834
47.9000 83.4000 82.1764 1.2236 1.2912 79.5115 84.8414
Corr. Coeff. = 0.991242; r*r = 0.982561
RMS Error = 3.676780; d.f = 24
Parameter Estimates...
p1= 0.814402 +/- 0.037871; p= 0.0000
p2= 82.245989 +/- 1.231129; p= 0.0000
Covariance Matrix Terms and Error-Correlations...
B(1,1)= 0.0014342477622406807; r= 1.0000
B(1,2)=B(2,1)= 0.027352558216794522; r= 0.5867
B(2,2)= 1.5156781067472096; r= 1.0000
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Experimental Data set{26}/trans-resveratrol
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0.00E+00,1.00E+02
1.81E+00,9.48E+01
3.02E+00,8.96E+01
4.11E+00,8.49E+01
5.56E+00,7.97E+01
6.77E+00,7.51E+01
8.10E+00,6.99E+01
1.00E+01,6.36E+01
1.26E+01,5.69E+01
1.43E+01,5.32E+01
1.58E+01,4.91E+01
1.74E+01,4.44E+01
1.96E+01,4.02E+01
2.22E+01,3.71E+01
2.51E+01,3.34E+01
2.77E+01,3.03E+01
3.03E+01,2.71E+01
3.22E+01,2.45E+01
3.48E+01,2.29E+01
3.74E+01,2.19E+01
4.03E+01,2.13E+01
4.28E+01,2.13E+01
4.58E+01,1.92E+01
4.78E+01,1.92E+01
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Experimental Data set{24}/trans-resveratrol Fixed p = "Not fixed"
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y = a-(Exp(b) * Power((t/48.0),b)*Exp( - b * (t/48.0))*c)
x1 y yc y-yc SEest YcLo YcHi
0.0000 100.0000 99.9086 0.0914 1.4222 96.9510 102.8663
1.8100 94.8000 92.3114 2.4886 0.7891 90.6703 93.9525
3.0200 89.6000 87.3890 2.2110 0.6510 86.0353 88.7428
4.1100 84.9000 83.1276 1.7724 0.6047 81.8699 84.3852
5.5600 79.7000 77.7248 1.9752 0.5938 76.4899 78.9597
6.7700 75.1000 73.4504 1.6496 0.5974 72.2079 74.6928
8.1000 69.9000 68.9947 0.9053 0.5996 67.7478 70.2416
10.0000 63.6000 63.0592 0.5408 0.5906 61.8309 64.2874
12.6000 56.9000 55.7215 1.1785 0.5567 54.5638 56.8792
14.3000 53.2000 51.3887 1.8113 0.5266 50.2936 52.4838
15.8000 49.1000 47.8550 1.2450 0.4987 46.8179 48.8921
17.4000 44.4000 44.3711 0.0289 0.4708 43.3921 45.3500
19.6000 40.2000 40.0366 0.1634 0.4402 39.1213 40.9520
22.2000 37.1000 35.5511 1.5489 0.4216 34.6744 36.4277
25.1000 33.4000 31.2977 2.1023 0.4253 30.4132 32.1822
27.7000 30.3000 28.0992 2.2008 0.4460 27.1716 29.0268
30.3000 27.1000 25.4310 1.6690 0.4759 24.4414 26.4207
32.2000 24.5000 23.7901 0.7099 0.4998 22.7507 24.8295
34.8000 22.9000 21.9333 0.9667 0.5316 20.8278 23.0388
37.4000 21.9000 20.4887 1.4113 0.5596 19.3249 21.6525
40.3000 21.3000 19.3175 1.9825 0.5843 18.1024 20.5327
42.8000 21.3000 18.6445 2.6555 0.5993 17.3983 19.8908
45.8000 19.2000 18.2058 0.9942 0.6093 16.9387 19.4729
47.8000 19.2000 18.1157 1.0843 0.6114 16.8442 19.3871
Corr. Coeff. = 0.998223; r*r = 0.996449
RMS Error = 1.679535; d.f = 21
Parameter Estimates...
p1= 99.978206 +/- 1.365578; p= 0.0000
p2= 1.026270 +/- 0.040327; p= 0.0000
p3= 81.793722 +/- 1.366146; p= 0.0000
Covariance Matrix Terms and Error-Correlations...
B(1,1)= 1.8648029851383043; r= 1.0000
B(1,2)=B(2,1)= -0.04572391632336313; r=-0.8303
B(1,3)=B(3,1)= 1.6932685722040636; r= 0.9076
B(2,2)= 0.0016262754961346025; r= 1.0000
B(2,3)=B(3,2)= -0.034468587244747835; r=-0.6256
B(3,3)= 1.8663543062516234; r= 1.0000
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Experimental Data set{24}/trans-resveratrol Fixed p = 0.81 <---------------X
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y = a-(Exp(0.81) * Power((t/48.0),0.81)*Exp( - 0.81 * (t/48.0))*b)
x1 y yc y-yc SEest YcLo YcHi
0.0000 100.0000 99.9802 0.0198 3.3143 93.1068 106.8536
1.8100 94.8000 87.3105 7.4895 2.7037 81.7034 92.9176
3.0200 89.6000 81.1877 8.4123 2.4225 76.1637 86.2117
4.1100 84.9000 76.2991 8.6009 2.2078 71.7205 80.8778
5.5600 79.7000 70.4631 9.2369 1.9670 66.3837 74.5425
6.7700 75.1000 66.0589 9.0411 1.8005 62.3249 69.7929
8.1000 69.9000 61.6253 8.2747 1.6505 58.2024 65.0481
10.0000 63.6000 55.9223 7.6777 1.4920 52.8281 59.0166
12.6000 56.9000 49.1328 7.7672 1.3711 46.2893 51.9762
14.3000 53.2000 45.2368 7.9632 1.3424 42.4527 48.0208
15.8000 49.1000 42.1134 6.9866 1.3430 39.3283 44.8986
17.4000 44.4000 39.0776 5.3224 1.3636 36.2497 41.9055
19.6000 40.2000 35.3560 4.8440 1.4145 32.4226 38.2895
22.2000 37.1000 31.5640 5.5360 1.4925 28.4687 34.6593
25.1000 33.4000 28.0195 5.3805 1.5860 24.7303 31.3086
27.7000 30.3000 25.3845 4.9155 1.6663 21.9288 28.8402
30.3000 27.1000 23.2054 3.8946 1.7387 19.5995 26.8112
32.2000 24.5000 21.8734 2.6266 1.7853 18.1709 25.5759
34.8000 22.9000 20.3734 2.5266 1.8397 16.5580 24.1888
37.4000 21.9000 19.2116 2.6884 1.8832 15.3061 23.1172
40.3000 21.3000 18.2730 3.0270 1.9191 14.2930 22.2530
42.8000 21.3000 17.7349 3.5651 1.9400 13.7117 21.7582
45.8000 19.2000 17.3847 1.8153 1.9537 13.3331 21.4364
47.8000 19.2000 17.3128 1.8872 1.9565 13.2553 21.3703
Corr. Coeff. = 0.974747; r*r = 0.950132
RMS Error = 6.280661; d.f = 22
Parameter Estimates...
p1= 100.404621 +/- 3.170769; p= 0.0000
p2= 82.895367 +/- 4.263856; p= 0.0000 <---------------X (Original %)
Covariance Matrix Terms and Error-Correlations...
B(1,1)= 10.053774103357764; r= 1.0000
B(1,2)=B(2,1)= 12.365301005728241; r= 0.9146
B(2,2)= 18.18046787331154; r= 1.0000
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