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- 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
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