| 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 |