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+NIST/ITL StRD
+Dataset Name: Gauss1 (Gauss1.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 48)
+ Certified Values (lines 41 to 53)
+ Data (lines 61 to 310)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: The data are two well-separated Gaussians on a
+ decaying exponential baseline plus normally
+ distributed zero-mean noise with variance = 6.25.
+
+Reference: Rust, B., NIST (1996).
+
+
+
+
+
+
+
+
+
+Data: 1 Response (y)
+ 1 Predictor (x)
+ 250 Observations
+ Lower Level of Difficulty
+ Generated Data
+
+Model: Exponential Class
+ 8 Parameters (b1 to b8)
+
+ y = b1*exp( -b2*x ) + b3*exp( -(x-b4)**2 / b5**2 )
+ + b6*exp( -(x-b7)**2 / b8**2 ) + e
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 97.0 94.0 9.8778210871E+01 5.7527312730E-01
+ b2 = 0.009 0.0105 1.0497276517E-02 1.1406289017E-04
+ b3 = 100.0 99.0 1.0048990633E+02 5.8831775752E-01
+ b4 = 65.0 63.0 6.7481111276E+01 1.0460593412E-01
+ b5 = 20.0 25.0 2.3129773360E+01 1.7439951146E-01
+ b6 = 70.0 71.0 7.1994503004E+01 6.2622793913E-01
+ b7 = 178.0 180.0 1.7899805021E+02 1.2436988217E-01
+ b8 = 16.5 20.0 1.8389389025E+01 2.0134312832E-01
+
+Residual Sum of Squares: 1.3158222432E+03
+Residual Standard Deviation: 2.3317980180E+00
+Degrees of Freedom: 242
+Number of Observations: 250
+
+
+
+
+
+
+Data: y x
+ 97.62227 1.000000
+ 97.80724 2.000000
+ 96.62247 3.000000
+ 92.59022 4.000000
+ 91.23869 5.000000
+ 95.32704 6.000000
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