| Sameer Agarwal | ea11704 | 2012-08-29 18:18:48 -0700 | [diff] [blame] | 1 | NIST/ITL StRD
|
| 2 | Dataset Name: MGH10 (MGH10.dat)
|
| 3 |
|
| 4 | File Format: ASCII
|
| 5 | Starting Values (lines 41 to 43)
|
| 6 | Certified Values (lines 41 to 48)
|
| 7 | Data (lines 61 to 76)
|
| 8 |
|
| 9 | Procedure: Nonlinear Least Squares Regression
|
| 10 |
|
| 11 | Description: This problem was found to be difficult for some very
|
| 12 | good algorithms.
|
| 13 |
|
| 14 | See More, J. J., Garbow, B. S., and Hillstrom, K. E.
|
| 15 | (1981). Testing unconstrained optimization software.
|
| 16 | ACM Transactions on Mathematical Software. 7(1):
|
| 17 | pp. 17-41.
|
| 18 |
|
| 19 | Reference: Meyer, R. R. (1970).
|
| 20 | Theoretical and computational aspects of nonlinear
|
| 21 | regression. In Nonlinear Programming, Rosen,
|
| 22 | Mangasarian and Ritter (Eds).
|
| 23 | New York, NY: Academic Press, pp. 465-486.
|
| 24 |
|
| 25 | Data: 1 Response (y)
|
| 26 | 1 Predictor (x)
|
| 27 | 16 Observations
|
| 28 | Higher Level of Difficulty
|
| 29 | Generated Data
|
| 30 |
|
| 31 | Model: Exponential Class
|
| 32 | 3 Parameters (b1 to b3)
|
| 33 |
|
| 34 | y = b1 * exp[b2/(x+b3)] + e
|
| 35 |
|
| 36 |
|
| 37 |
|
| 38 | Starting values Certified Values
|
| 39 |
|
| 40 | Start 1 Start 2 Parameter Standard Deviation
|
| 41 | b1 = 2 0.02 5.6096364710E-03 1.5687892471E-04
|
| 42 | b2 = 400000 4000 6.1813463463E+03 2.3309021107E+01
|
| 43 | b3 = 25000 250 3.4522363462E+02 7.8486103508E-01
|
| 44 |
|
| 45 | Residual Sum of Squares: 8.7945855171E+01
|
| 46 | Residual Standard Deviation: 2.6009740065E+00
|
| 47 | Degrees of Freedom: 13
|
| 48 | Number of Observations: 16
|
| 49 |
|
| 50 |
|
| 51 |
|
| 52 |
|
| 53 |
|
| 54 |
|
| 55 |
|
| 56 |
|
| 57 |
|
| 58 |
|
| 59 |
|
| 60 | Data: y x
|
| 61 | 3.478000E+04 5.000000E+01
|
| 62 | 2.861000E+04 5.500000E+01
|
| 63 | 2.365000E+04 6.000000E+01
|
| 64 | 1.963000E+04 6.500000E+01
|
| 65 | 1.637000E+04 7.000000E+01
|
| 66 | 1.372000E+04 7.500000E+01
|
| 67 | 1.154000E+04 8.000000E+01
|
| 68 | 9.744000E+03 8.500000E+01
|
| 69 | 8.261000E+03 9.000000E+01
|
| 70 | 7.030000E+03 9.500000E+01
|
| 71 | 6.005000E+03 1.000000E+02
|
| 72 | 5.147000E+03 1.050000E+02
|
| 73 | 4.427000E+03 1.100000E+02
|
| 74 | 3.820000E+03 1.150000E+02
|
| 75 | 3.307000E+03 1.200000E+02
|
| 76 | 2.872000E+03 1.250000E+02
|
