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+NIST/ITL StRD
+Dataset Name:  MGH10             (MGH10.dat)
+
+File Format:   ASCII
+               Starting Values   (lines 41 to 43)
+               Certified Values  (lines 41 to 48)
+               Data              (lines 61 to 76)
+
+Procedure:     Nonlinear Least Squares Regression
+
+Description:   This problem was found to be difficult for some very
+               good algorithms.
+
+               See More, J. J., Garbow, B. S., and Hillstrom, K. E. 
+               (1981).  Testing unconstrained optimization software.
+               ACM Transactions on Mathematical Software. 7(1): 
+               pp. 17-41.
+
+Reference:     Meyer, R. R. (1970).  
+               Theoretical and computational aspects of nonlinear 
+               regression.  In Nonlinear Programming, Rosen, 
+               Mangasarian and Ritter (Eds).  
+               New York, NY: Academic Press, pp. 465-486.
+
+Data:          1 Response  (y)
+               1 Predictor (x)
+               16 Observations
+               Higher Level of Difficulty
+               Generated Data
+ 
+Model:         Exponential Class
+               3 Parameters (b1 to b3)
+ 
+               y = b1 * exp[b2/(x+b3)]  +  e
+
+
+
+          Starting values                  Certified Values
+
+        Start 1     Start 2           Parameter     Standard Deviation
+  b1 =        2         0.02       5.6096364710E-03  1.5687892471E-04
+  b2 =   400000      4000          6.1813463463E+03  2.3309021107E+01
+  b3 =    25000       250          3.4522363462E+02  7.8486103508E-01
+
+Residual Sum of Squares:                    8.7945855171E+01
+Residual Standard Deviation:                2.6009740065E+00
+Degrees of Freedom:                                13
+Number of Observations:                            16
+
+
+
+
+
+
+
+
+
+
+
+Data:  y               x
+      3.478000E+04    5.000000E+01
+      2.861000E+04    5.500000E+01
+      2.365000E+04    6.000000E+01
+      1.963000E+04    6.500000E+01
+      1.637000E+04    7.000000E+01
+      1.372000E+04    7.500000E+01
+      1.154000E+04    8.000000E+01
+      9.744000E+03    8.500000E+01
+      8.261000E+03    9.000000E+01
+      7.030000E+03    9.500000E+01
+      6.005000E+03    1.000000E+02
+      5.147000E+03    1.050000E+02
+      4.427000E+03    1.100000E+02
+      3.820000E+03    1.150000E+02
+      3.307000E+03    1.200000E+02
+      2.872000E+03    1.250000E+02