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0001 NIST/ITL StRD 0002 Dataset Name: MGH09 (MGH09.dat) 0003 0004 File Format: ASCII 0005 Starting Values (lines 41 to 44) 0006 Certified Values (lines 41 to 49) 0007 Data (lines 61 to 71) 0008 0009 Procedure: Nonlinear Least Squares Regression 0010 0011 Description: This problem was found to be difficult for some very 0012 good algorithms. There is a local minimum at (+inf, 0013 -14.07..., -inf, -inf) with final sum of squares 0014 0.00102734.... 0015 0016 See More, J. J., Garbow, B. S., and Hillstrom, K. E. 0017 (1981). Testing unconstrained optimization software. 0018 ACM Transactions on Mathematical Software. 7(1): 0019 pp. 17-41. 0020 0021 Reference: Kowalik, J.S., and M. R. Osborne, (1978). 0022 Methods for Unconstrained Optimization Problems. 0023 New York, NY: Elsevier North-Holland. 0024 0025 Data: 1 Response (y) 0026 1 Predictor (x) 0027 11 Observations 0028 Higher Level of Difficulty 0029 Generated Data 0030 0031 Model: Rational Class (linear/quadratic) 0032 4 Parameters (b1 to b4) 0033 0034 y = b1*(x**2+x*b2) / (x**2+x*b3+b4) + e 0035 0036 0037 0038 Starting values Certified Values 0039 0040 Start 1 Start 2 Parameter Standard Deviation 0041 b1 = 25 0.25 1.9280693458E-01 1.1435312227E-02 0042 b2 = 39 0.39 1.9128232873E-01 1.9633220911E-01 0043 b3 = 41.5 0.415 1.2305650693E-01 8.0842031232E-02 0044 b4 = 39 0.39 1.3606233068E-01 9.0025542308E-02 0045 0046 Residual Sum of Squares: 3.0750560385E-04 0047 Residual Standard Deviation: 6.6279236551E-03 0048 Degrees of Freedom: 7 0049 Number of Observations: 11 0050 0051 0052 0053 0054 0055 0056 0057 0058 0059 0060 Data: y x 0061 1.957000E-01 4.000000E+00 0062 1.947000E-01 2.000000E+00 0063 1.735000E-01 1.000000E+00 0064 1.600000E-01 5.000000E-01 0065 8.440000E-02 2.500000E-01 0066 6.270000E-02 1.670000E-01 0067 4.560000E-02 1.250000E-01 0068 3.420000E-02 1.000000E-01 0069 3.230000E-02 8.330000E-02 0070 2.350000E-02 7.140000E-02 0071 2.460000E-02 6.250000E-02