NIST/ITL StRD | |
Dataset Name: MGH10 (MGH10.dat) | |
File Format: ASCII | |
Starting Values (lines 41 to 43) | |
Certified Values (lines 41 to 48) | |
Data (lines 61 to 76) | |
Procedure: Nonlinear Least Squares Regression | |
Description: This problem was found to be difficult for some very | |
good algorithms. | |
See More, J. J., Garbow, B. S., and Hillstrom, K. E. | |
(1981). Testing unconstrained optimization software. | |
ACM Transactions on Mathematical Software. 7(1): | |
pp. 17-41. | |
Reference: Meyer, R. R. (1970). | |
Theoretical and computational aspects of nonlinear | |
regression. In Nonlinear Programming, Rosen, | |
Mangasarian and Ritter (Eds). | |
New York, NY: Academic Press, pp. 465-486. | |
Data: 1 Response (y) | |
1 Predictor (x) | |
16 Observations | |
Higher Level of Difficulty | |
Generated Data | |
Model: Exponential Class | |
3 Parameters (b1 to b3) | |
y = b1 * exp[b2/(x+b3)] + e | |
Starting values Certified Values | |
Start 1 Start 2 Parameter Standard Deviation | |
b1 = 2 0.02 5.6096364710E-03 1.5687892471E-04 | |
b2 = 400000 4000 6.1813463463E+03 2.3309021107E+01 | |
b3 = 25000 250 3.4522363462E+02 7.8486103508E-01 | |
Residual Sum of Squares: 8.7945855171E+01 | |
Residual Standard Deviation: 2.6009740065E+00 | |
Degrees of Freedom: 13 | |
Number of Observations: 16 | |
Data: y x | |
3.478000E+04 5.000000E+01 | |
2.861000E+04 5.500000E+01 | |
2.365000E+04 6.000000E+01 | |
1.963000E+04 6.500000E+01 | |
1.637000E+04 7.000000E+01 | |
1.372000E+04 7.500000E+01 | |
1.154000E+04 8.000000E+01 | |
9.744000E+03 8.500000E+01 | |
8.261000E+03 9.000000E+01 | |
7.030000E+03 9.500000E+01 | |
6.005000E+03 1.000000E+02 | |
5.147000E+03 1.050000E+02 | |
4.427000E+03 1.100000E+02 | |
3.820000E+03 1.150000E+02 | |
3.307000E+03 1.200000E+02 | |
2.872000E+03 1.250000E+02 |