72 lines
2.3 KiB
Plaintext
72 lines
2.3 KiB
Plaintext
NIST/ITL StRD
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Dataset Name: MGH09 (MGH09.dat)
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File Format: ASCII
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Starting Values (lines 41 to 44)
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Certified Values (lines 41 to 49)
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Data (lines 61 to 71)
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Procedure: Nonlinear Least Squares Regression
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Description: This problem was found to be difficult for some very
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good algorithms. There is a local minimum at (+inf,
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-14.07..., -inf, -inf) with final sum of squares
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0.00102734....
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See More, J. J., Garbow, B. S., and Hillstrom, K. E.
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(1981). Testing unconstrained optimization software.
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ACM Transactions on Mathematical Software. 7(1):
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pp. 17-41.
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Reference: Kowalik, J.S., and M. R. Osborne, (1978).
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Methods for Unconstrained Optimization Problems.
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New York, NY: Elsevier North-Holland.
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Data: 1 Response (y)
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1 Predictor (x)
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11 Observations
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Higher Level of Difficulty
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Generated Data
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Model: Rational Class (linear/quadratic)
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4 Parameters (b1 to b4)
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y = b1*(x**2+x*b2) / (x**2+x*b3+b4) + e
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Starting values Certified Values
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Start 1 Start 2 Parameter Standard Deviation
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b1 = 25 0.25 1.9280693458E-01 1.1435312227E-02
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b2 = 39 0.39 1.9128232873E-01 1.9633220911E-01
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b3 = 41.5 0.415 1.2305650693E-01 8.0842031232E-02
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b4 = 39 0.39 1.3606233068E-01 9.0025542308E-02
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Residual Sum of Squares: 3.0750560385E-04
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Residual Standard Deviation: 6.6279236551E-03
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Degrees of Freedom: 7
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Number of Observations: 11
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Data: y x
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1.957000E-01 4.000000E+00
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1.947000E-01 2.000000E+00
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1.735000E-01 1.000000E+00
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1.600000E-01 5.000000E-01
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8.440000E-02 2.500000E-01
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6.270000E-02 1.670000E-01
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4.560000E-02 1.250000E-01
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3.420000E-02 1.000000E-01
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3.230000E-02 8.330000E-02
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2.350000E-02 7.140000E-02
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2.460000E-02 6.250000E-02
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