2 Dataset Name: Gauss3 (Gauss3.dat)
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5 Starting Values (lines 41 to 48)
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6 Certified Values (lines 41 to 53)
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7 Data (lines 61 to 310)
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9 Procedure: Nonlinear Least Squares Regression
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11 Description: The data are two strongly-blended Gaussians on a
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12 decaying exponential baseline plus normally
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13 distributed zero-mean noise with variance = 6.25.
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15 Reference: Rust, B., NIST (1996).
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25 Data: 1 Response (y)
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28 Average Level of Difficulty
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31 Model: Exponential Class
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32 8 Parameters (b1 to b8)
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34 y = b1*exp( -b2*x ) + b3*exp( -(x-b4)**2 / b5**2 )
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35 + b6*exp( -(x-b7)**2 / b8**2 ) + e
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38 Starting values Certified Values
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40 Start 1 Start 2 Parameter Standard Deviation
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41 b1 = 94.9 96.0 9.8940368970E+01 5.3005192833E-01
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42 b2 = 0.009 0.0096 1.0945879335E-02 1.2554058911E-04
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43 b3 = 90.1 80.0 1.0069553078E+02 8.1256587317E-01
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44 b4 = 113.0 110.0 1.1163619459E+02 3.5317859757E-01
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45 b5 = 20.0 25.0 2.3300500029E+01 3.6584783023E-01
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46 b6 = 73.8 74.0 7.3705031418E+01 1.2091239082E+00
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47 b7 = 140.0 139.0 1.4776164251E+02 4.0488183351E-01
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48 b8 = 20.0 25.0 1.9668221230E+01 3.7806634336E-01
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50 Residual Sum of Squares: 1.2444846360E+03
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51 Residual Standard Deviation: 2.2677077625E+00
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52 Degrees of Freedom: 242
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53 Number of Observations: 250
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