Basic harness for testing NIST problems.
Change-Id: I5baaa24dbf0506ceedf4a9be4ed17c84974d71a1
diff --git a/data/nist/Bennett5.dat b/data/nist/Bennett5.dat
new file mode 100644
index 0000000..eba218a
--- /dev/null
+++ b/data/nist/Bennett5.dat
@@ -0,0 +1,214 @@
+NIST/ITL StRD
+Dataset Name: Bennett5 (Bennett5.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 43)
+ Certified Values (lines 41 to 48)
+ Data (lines 61 to 214)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ superconductivity magnetization modeling. The
+ response variable is magnetism, and the predictor
+ variable is the log of time in minutes.
+
+Reference: Bennett, L., L. Swartzendruber, and H. Brown,
+ NIST (1994).
+ Superconductivity Magnetization Modeling.
+
+
+
+
+
+
+Data: 1 Response Variable (y = magnetism)
+ 1 Predictor Variable (x = log[time])
+ 154 Observations
+ Higher Level of Difficulty
+ Observed Data
+
+Model: Miscellaneous Class
+ 3 Parameters (b1 to b3)
+
+ y = b1 * (b2+x)**(-1/b3) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = -2000 -1500 -2.5235058043E+03 2.9715175411E+02
+ b2 = 50 45 4.6736564644E+01 1.2448871856E+00
+ b3 = 0.8 0.85 9.3218483193E-01 2.0272299378E-02
+
+Residual Sum of Squares: 5.2404744073E-04
+Residual Standard Deviation: 1.8629312528E-03
+Degrees of Freedom: 151
+Number of Observations: 154
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ -34.834702E0 7.447168E0
+ -34.393200E0 8.102586E0
+ -34.152901E0 8.452547E0
+ -33.979099E0 8.711278E0
+ -33.845901E0 8.916774E0
+ -33.732899E0 9.087155E0
+ -33.640301E0 9.232590E0
+ -33.559200E0 9.359535E0
+ -33.486801E0 9.472166E0
+ -33.423100E0 9.573384E0
+ -33.365101E0 9.665293E0
+ -33.313000E0 9.749461E0
+ -33.260899E0 9.827092E0
+ -33.217400E0 9.899128E0
+ -33.176899E0 9.966321E0
+ -33.139198E0 10.029280E0
+ -33.101601E0 10.088510E0
+ -33.066799E0 10.144430E0
+ -33.035000E0 10.197380E0
+ -33.003101E0 10.247670E0
+ -32.971298E0 10.295560E0
+ -32.942299E0 10.341250E0
+ -32.916302E0 10.384950E0
+ -32.890202E0 10.426820E0
+ -32.864101E0 10.467000E0
+ -32.841000E0 10.505640E0
+ -32.817799E0 10.542830E0
+ -32.797501E0 10.578690E0
+ -32.774300E0 10.613310E0
+ -32.757000E0 10.646780E0
+ -32.733799E0 10.679150E0
+ -32.716400E0 10.710520E0
+ -32.699100E0 10.740920E0
+ -32.678799E0 10.770440E0
+ -32.661400E0 10.799100E0
+ -32.644001E0 10.826970E0
+ -32.626701E0 10.854080E0
+ -32.612202E0 10.880470E0
+ -32.597698E0 10.906190E0
+ -32.583199E0 10.931260E0
+ -32.568699E0 10.955720E0
+ -32.554298E0 10.979590E0
+ -32.539799E0 11.002910E0
+ -32.525299E0 11.025700E0
+ -32.510799E0 11.047980E0
+ -32.499199E0 11.069770E0
+ -32.487598E0 11.091100E0
+ -32.473202E0 11.111980E0
+ -32.461601E0 11.132440E0
+ -32.435501E0 11.152480E0
+ -32.435501E0 11.172130E0
+ -32.426800E0 11.191410E0
+ -32.412300E0 11.210310E0
+ -32.400799E0 11.228870E0
+ -32.392101E0 11.247090E0
+ -32.380501E0 11.264980E0
+ -32.366001E0 11.282560E0
+ -32.357300E0 11.299840E0
+ -32.348598E0 11.316820E0
+ -32.339901E0 11.333520E0
+ -32.328400E0 11.349940E0
+ -32.319698E0 11.366100E0
+ -32.311001E0 11.382000E0
+ -32.299400E0 11.397660E0
+ -32.290699E0 11.413070E0
+ -32.282001E0 11.428240E0
+ -32.273300E0 11.443200E0
+ -32.264599E0 11.457930E0
+ -32.256001E0 11.472440E0
+ -32.247299E0 11.486750E0
+ -32.238602E0 11.500860E0
+ -32.229900E0 11.514770E0
+ -32.224098E0 11.528490E0
+ -32.215401E0 11.542020E0
+ -32.203800E0 11.555380E0
+ -32.198002E0 11.568550E0
+ -32.189400E0 11.581560E0
+ -32.183601E0 11.594420E0
+ -32.174900E0 11.607121E0
+ -32.169102E0 11.619640E0
+ -32.163300E0 11.632000E0
+ -32.154598E0 11.644210E0
+ -32.145901E0 11.656280E0
+ -32.140099E0 11.668200E0
+ -32.131401E0 11.679980E0
+ -32.125599E0 11.691620E0
+ -32.119801E0 11.703130E0
+ -32.111198E0 11.714510E0
+ -32.105400E0 11.725760E0
+ -32.096699E0 11.736880E0
+ -32.090900E0 11.747890E0
+ -32.088001E0 11.758780E0
+ -32.079300E0 11.769550E0
+ -32.073502E0 11.780200E0
+ -32.067699E0 11.790730E0
+ -32.061901E0 11.801160E0
+ -32.056099E0 11.811480E0
+ -32.050301E0 11.821700E0
+ -32.044498E0 11.831810E0
+ -32.038799E0 11.841820E0
+ -32.033001E0 11.851730E0
+ -32.027199E0 11.861550E0
+ -32.024300E0 11.871270E0
+ -32.018501E0 11.880890E0
+ -32.012699E0 11.890420E0
+ -32.004002E0 11.899870E0
+ -32.001099E0 11.909220E0
+ -31.995300E0 11.918490E0
+ -31.989500E0 11.927680E0
+ -31.983700E0 11.936780E0
+ -31.977900E0 11.945790E0
+ -31.972099E0 11.954730E0
+ -31.969299E0 11.963590E0
+ -31.963501E0 11.972370E0
+ -31.957701E0 11.981070E0
+ -31.951900E0 11.989700E0
+ -31.946100E0 11.998260E0
+ -31.940300E0 12.006740E0
+ -31.937401E0 12.015150E0
+ -31.931601E0 12.023490E0
+ -31.925800E0 12.031760E0
+ -31.922899E0 12.039970E0
+ -31.917101E0 12.048100E0
+ -31.911301E0 12.056170E0
+ -31.908400E0 12.064180E0
+ -31.902599E0 12.072120E0
+ -31.896900E0 12.080010E0
+ -31.893999E0 12.087820E0
+ -31.888201E0 12.095580E0
+ -31.885300E0 12.103280E0
+ -31.882401E0 12.110920E0
+ -31.876600E0 12.118500E0
+ -31.873699E0 12.126030E0
+ -31.867901E0 12.133500E0
+ -31.862101E0 12.140910E0
+ -31.859200E0 12.148270E0
+ -31.856300E0 12.155570E0
+ -31.850500E0 12.162830E0
+ -31.844700E0 12.170030E0
+ -31.841801E0 12.177170E0
+ -31.838900E0 12.184270E0
+ -31.833099E0 12.191320E0
+ -31.830200E0 12.198320E0
+ -31.827299E0 12.205270E0
+ -31.821600E0 12.212170E0
+ -31.818701E0 12.219030E0
+ -31.812901E0 12.225840E0
+ -31.809999E0 12.232600E0
+ -31.807100E0 12.239320E0
+ -31.801300E0 12.245990E0
+ -31.798401E0 12.252620E0
+ -31.795500E0 12.259200E0
+ -31.789700E0 12.265750E0
+ -31.786800E0 12.272240E0
diff --git a/data/nist/BoxBOD.dat b/data/nist/BoxBOD.dat
new file mode 100644
index 0000000..6a742fd
--- /dev/null
+++ b/data/nist/BoxBOD.dat
@@ -0,0 +1,66 @@
+NIST/ITL StRD
+Dataset Name: BoxBOD (BoxBOD.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 42)
+ Certified Values (lines 41 to 47)
+ Data (lines 61 to 66)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are described in detail in Box, Hunter and
+ Hunter (1978). The response variable is biochemical
+ oxygen demand (BOD) in mg/l, and the predictor
+ variable is incubation time in days.
+
+
+Reference: Box, G. P., W. G. Hunter, and J. S. Hunter (1978).
+ Statistics for Experimenters.
+ New York, NY: Wiley, pp. 483-487.
+
+
+
+
+
+Data: 1 Response (y = biochemical oxygen demand)
+ 1 Predictor (x = incubation time)
+ 6 Observations
+ Higher Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 2 Parameters (b1 and b2)
+
+ y = b1*(1-exp[-b2*x]) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 1 100 2.1380940889E+02 1.2354515176E+01
+ b2 = 1 0.75 5.4723748542E-01 1.0455993237E-01
+
+Residual Sum of Squares: 1.1680088766E+03
+Residual Standard Deviation: 1.7088072423E+01
+Degrees of Freedom: 4
+Number of Observations: 6
+
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 109 1
+ 149 2
+ 149 3
+ 191 5
+ 213 7
+ 224 10
diff --git a/data/nist/Chwirut1.dat b/data/nist/Chwirut1.dat
new file mode 100644
index 0000000..4ad8aa5
--- /dev/null
+++ b/data/nist/Chwirut1.dat
@@ -0,0 +1,274 @@
+NIST/ITL StRD
+Dataset Name: Chwirut1 (Chwirut1.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 43)
+ Certified Values (lines 41 to 48)
+ Data (lines 61 to 274)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ ultrasonic calibration. The response variable is
+ ultrasonic response, and the predictor variable is
+ metal distance.
+
+Reference: Chwirut, D., NIST (197?).
+ Ultrasonic Reference Block Study.
+
+
+
+
+
+
+
+Data: 1 Response Variable (y = ultrasonic response)
+ 1 Predictor Variable (x = metal distance)
+ 214 Observations
+ Lower Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 3 Parameters (b1 to b3)
+
+ y = exp[-b1*x]/(b2+b3*x) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 0.1 0.15 1.9027818370E-01 2.1938557035E-02
+ b2 = 0.01 0.008 6.1314004477E-03 3.4500025051E-04
+ b3 = 0.02 0.010 1.0530908399E-02 7.9281847748E-04
+
+Residual Sum of Squares: 2.3844771393E+03
+Residual Standard Deviation: 3.3616721320E+00
+Degrees of Freedom: 211
+Number of Observations: 214
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 92.9000E0 0.5000E0
+ 78.7000E0 0.6250E0
+ 64.2000E0 0.7500E0
+ 64.9000E0 0.8750E0
+ 57.1000E0 1.0000E0
+ 43.3000E0 1.2500E0
+ 31.1000E0 1.7500E0
+ 23.6000E0 2.2500E0
+ 31.0500E0 1.7500E0
+ 23.7750E0 2.2500E0
+ 17.7375E0 2.7500E0
+ 13.8000E0 3.2500E0
+ 11.5875E0 3.7500E0
+ 9.4125E0 4.2500E0
+ 7.7250E0 4.7500E0
+ 7.3500E0 5.2500E0
+ 8.0250E0 5.7500E0
+ 90.6000E0 0.5000E0
+ 76.9000E0 0.6250E0
+ 71.6000E0 0.7500E0
+ 63.6000E0 0.8750E0
+ 54.0000E0 1.0000E0
+ 39.2000E0 1.2500E0
+ 29.3000E0 1.7500E0
+ 21.4000E0 2.2500E0
+ 29.1750E0 1.7500E0
+ 22.1250E0 2.2500E0
+ 17.5125E0 2.7500E0
+ 14.2500E0 3.2500E0
+ 9.4500E0 3.7500E0
+ 9.1500E0 4.2500E0
+ 7.9125E0 4.7500E0
+ 8.4750E0 5.2500E0
+ 6.1125E0 5.7500E0
+ 80.0000E0 0.5000E0
+ 79.0000E0 0.6250E0
+ 63.8000E0 0.7500E0
+ 57.2000E0 0.8750E0
+ 53.2000E0 1.0000E0
+ 42.5000E0 1.2500E0
+ 26.8000E0 1.7500E0
+ 20.4000E0 2.2500E0
+ 26.8500E0 1.7500E0
+ 21.0000E0 2.2500E0
+ 16.4625E0 2.7500E0
+ 12.5250E0 3.2500E0
+ 10.5375E0 3.7500E0
+ 8.5875E0 4.2500E0
+ 7.1250E0 4.7500E0
+ 6.1125E0 5.2500E0
+ 5.9625E0 5.7500E0
+ 74.1000E0 0.5000E0
+ 67.3000E0 0.6250E0
+ 60.8000E0 0.7500E0
+ 55.5000E0 0.8750E0
+ 50.3000E0 1.0000E0
+ 41.0000E0 1.2500E0
+ 29.4000E0 1.7500E0
+ 20.4000E0 2.2500E0
+ 29.3625E0 1.7500E0
+ 21.1500E0 2.2500E0
+ 16.7625E0 2.7500E0
+ 13.2000E0 3.2500E0
+ 10.8750E0 3.7500E0
+ 8.1750E0 4.2500E0
+ 7.3500E0 4.7500E0
+ 5.9625E0 5.2500E0
+ 5.6250E0 5.7500E0
+ 81.5000E0 .5000E0
+ 62.4000E0 .7500E0
+ 32.5000E0 1.5000E0
+ 12.4100E0 3.0000E0
+ 13.1200E0 3.0000E0
+ 15.5600E0 3.0000E0
+ 5.6300E0 6.0000E0
+ 78.0000E0 .5000E0
+ 59.9000E0 .7500E0
+ 33.2000E0 1.5000E0
+ 13.8400E0 3.0000E0
+ 12.7500E0 3.0000E0
+ 14.6200E0 3.0000E0
+ 3.9400E0 6.0000E0
+ 76.8000E0 .5000E0
+ 61.0000E0 .7500E0
+ 32.9000E0 1.5000E0
+ 13.8700E0 3.0000E0
+ 11.8100E0 3.0000E0
+ 13.3100E0 3.0000E0
+ 5.4400E0 6.0000E0
+ 78.0000E0 .5000E0
+ 63.5000E0 .7500E0
+ 33.8000E0 1.5000E0
+ 12.5600E0 3.0000E0
+ 5.6300E0 6.0000E0
+ 12.7500E0 3.0000E0
+ 13.1200E0 3.0000E0
+ 5.4400E0 6.0000E0
+ 76.8000E0 .5000E0
+ 60.0000E0 .7500E0
+ 47.8000E0 1.0000E0
+ 32.0000E0 1.5000E0
+ 22.2000E0 2.0000E0
+ 22.5700E0 2.0000E0
+ 18.8200E0 2.5000E0
+ 13.9500E0 3.0000E0
+ 11.2500E0 4.0000E0
+ 9.0000E0 5.0000E0
+ 6.6700E0 6.0000E0
+ 75.8000E0 .5000E0
+ 62.0000E0 .7500E0
+ 48.8000E0 1.0000E0
+ 35.2000E0 1.5000E0
+ 20.0000E0 2.0000E0
+ 20.3200E0 2.0000E0
+ 19.3100E0 2.5000E0
+ 12.7500E0 3.0000E0
+ 10.4200E0 4.0000E0
+ 7.3100E0 5.0000E0
+ 7.4200E0 6.0000E0
+ 70.5000E0 .5000E0
+ 59.5000E0 .7500E0
+ 48.5000E0 1.0000E0
+ 35.8000E0 1.5000E0
+ 21.0000E0 2.0000E0
+ 21.6700E0 2.0000E0
+ 21.0000E0 2.5000E0
+ 15.6400E0 3.0000E0
+ 8.1700E0 4.0000E0
+ 8.5500E0 5.0000E0
+ 10.1200E0 6.0000E0
+ 78.0000E0 .5000E0
+ 66.0000E0 .6250E0
+ 62.0000E0 .7500E0
+ 58.0000E0 .8750E0
+ 47.7000E0 1.0000E0
+ 37.8000E0 1.2500E0
+ 20.2000E0 2.2500E0
+ 21.0700E0 2.2500E0
+ 13.8700E0 2.7500E0
+ 9.6700E0 3.2500E0
+ 7.7600E0 3.7500E0
+ 5.4400E0 4.2500E0
+ 4.8700E0 4.7500E0
+ 4.0100E0 5.2500E0
+ 3.7500E0 5.7500E0
+ 24.1900E0 3.0000E0
+ 25.7600E0 3.0000E0
+ 18.0700E0 3.0000E0
+ 11.8100E0 3.0000E0
+ 12.0700E0 3.0000E0
+ 16.1200E0 3.0000E0
+ 70.8000E0 .5000E0
+ 54.7000E0 .7500E0
+ 48.0000E0 1.0000E0
+ 39.8000E0 1.5000E0
+ 29.8000E0 2.0000E0
+ 23.7000E0 2.5000E0
+ 29.6200E0 2.0000E0
+ 23.8100E0 2.5000E0
+ 17.7000E0 3.0000E0
+ 11.5500E0 4.0000E0
+ 12.0700E0 5.0000E0
+ 8.7400E0 6.0000E0
+ 80.7000E0 .5000E0
+ 61.3000E0 .7500E0
+ 47.5000E0 1.0000E0
+ 29.0000E0 1.5000E0
+ 24.0000E0 2.0000E0
+ 17.7000E0 2.5000E0
+ 24.5600E0 2.0000E0
+ 18.6700E0 2.5000E0
+ 16.2400E0 3.0000E0
+ 8.7400E0 4.0000E0
+ 7.8700E0 5.0000E0
+ 8.5100E0 6.0000E0
+ 66.7000E0 .5000E0
+ 59.2000E0 .7500E0
+ 40.8000E0 1.0000E0
+ 30.7000E0 1.5000E0
+ 25.7000E0 2.0000E0
+ 16.3000E0 2.5000E0
+ 25.9900E0 2.0000E0
+ 16.9500E0 2.5000E0
+ 13.3500E0 3.0000E0
+ 8.6200E0 4.0000E0
+ 7.2000E0 5.0000E0
+ 6.6400E0 6.0000E0
+ 13.6900E0 3.0000E0
+ 81.0000E0 .5000E0
+ 64.5000E0 .7500E0
+ 35.5000E0 1.5000E0
+ 13.3100E0 3.0000E0
+ 4.8700E0 6.0000E0
+ 12.9400E0 3.0000E0
+ 5.0600E0 6.0000E0
+ 15.1900E0 3.0000E0
+ 14.6200E0 3.0000E0
+ 15.6400E0 3.0000E0
+ 25.5000E0 1.7500E0
+ 25.9500E0 1.7500E0
+ 81.7000E0 .5000E0
+ 61.6000E0 .7500E0
+ 29.8000E0 1.7500E0
+ 29.8100E0 1.7500E0
+ 17.1700E0 2.7500E0
+ 10.3900E0 3.7500E0
+ 28.4000E0 1.7500E0
+ 28.6900E0 1.7500E0
+ 81.3000E0 .5000E0
+ 60.9000E0 .7500E0
+ 16.6500E0 2.7500E0
+ 10.0500E0 3.7500E0
+ 28.9000E0 1.7500E0
+ 28.9500E0 1.7500E0
diff --git a/data/nist/Chwirut2.dat b/data/nist/Chwirut2.dat
new file mode 100644
index 0000000..03703de
--- /dev/null
+++ b/data/nist/Chwirut2.dat
@@ -0,0 +1,114 @@
+NIST/ITL StRD
+Dataset Name: Chwirut2 (Chwirut2.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 43)
+ Certified Values (lines 41 to 48)
+ Data (lines 61 to 114)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ ultrasonic calibration. The response variable is
+ ultrasonic response, and the predictor variable is
+ metal distance.
+
+
+
+Reference: Chwirut, D., NIST (197?).
+ Ultrasonic Reference Block Study.
+
+
+
+
+
+Data: 1 Response (y = ultrasonic response)
+ 1 Predictor (x = metal distance)
+ 54 Observations
+ Lower Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 3 Parameters (b1 to b3)
+
+ y = exp(-b1*x)/(b2+b3*x) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 0.1 0.15 1.6657666537E-01 3.8303286810E-02
+ b2 = 0.01 0.008 5.1653291286E-03 6.6621605126E-04
+ b3 = 0.02 0.010 1.2150007096E-02 1.5304234767E-03
+
+Residual Sum of Squares: 5.1304802941E+02
+Residual Standard Deviation: 3.1717133040E+00
+Degrees of Freedom: 51
+Number of Observations: 54
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 92.9000E0 0.500E0
+ 57.1000E0 1.000E0
+ 31.0500E0 1.750E0
+ 11.5875E0 3.750E0
+ 8.0250E0 5.750E0
+ 63.6000E0 0.875E0
+ 21.4000E0 2.250E0
+ 14.2500E0 3.250E0
+ 8.4750E0 5.250E0
+ 63.8000E0 0.750E0
+ 26.8000E0 1.750E0
+ 16.4625E0 2.750E0
+ 7.1250E0 4.750E0
+ 67.3000E0 0.625E0
+ 41.0000E0 1.250E0
+ 21.1500E0 2.250E0
+ 8.1750E0 4.250E0
+ 81.5000E0 .500E0
+ 13.1200E0 3.000E0
+ 59.9000E0 .750E0
+ 14.6200E0 3.000E0
+ 32.9000E0 1.500E0
+ 5.4400E0 6.000E0
+ 12.5600E0 3.000E0
+ 5.4400E0 6.000E0
+ 32.0000E0 1.500E0
+ 13.9500E0 3.000E0
+ 75.8000E0 .500E0
+ 20.0000E0 2.000E0
+ 10.4200E0 4.000E0
+ 59.5000E0 .750E0
+ 21.6700E0 2.000E0
+ 8.5500E0 5.000E0
+ 62.0000E0 .750E0
+ 20.2000E0 2.250E0
+ 7.7600E0 3.750E0
+ 3.7500E0 5.750E0
+ 11.8100E0 3.000E0
+ 54.7000E0 .750E0
+ 23.7000E0 2.500E0
+ 11.5500E0 4.000E0
+ 61.3000E0 .750E0
+ 17.7000E0 2.500E0
+ 8.7400E0 4.000E0
+ 59.2000E0 .750E0
+ 16.3000E0 2.500E0
+ 8.6200E0 4.000E0
+ 81.0000E0 .500E0
+ 4.8700E0 6.000E0
+ 14.6200E0 3.000E0
+ 81.7000E0 .500E0
+ 17.1700E0 2.750E0
+ 81.3000E0 .500E0
+ 28.9000E0 1.750E0
diff --git a/data/nist/DanWood.dat b/data/nist/DanWood.dat
new file mode 100644
index 0000000..479a9bd
--- /dev/null
+++ b/data/nist/DanWood.dat
@@ -0,0 +1,66 @@
+NIST/ITL StRD
+Dataset Name: DanWood (DanWood.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 42)
+ Certified Values (lines 41 to 47)
+ Data (lines 61 to 66)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data and model are described in Daniel and Wood
+ (1980), and originally published in E.S.Keeping,
+ "Introduction to Statistical Inference," Van Nostrand
+ Company, Princeton, NJ, 1962, p. 354. The response
+ variable is energy radieted from a carbon filament
+ lamp per cm**2 per second, and the predictor variable
+ is the absolute temperature of the filament in 1000
+ degrees Kelvin.
+
+Reference: Daniel, C. and F. S. Wood (1980).
+ Fitting Equations to Data, Second Edition.
+ New York, NY: John Wiley and Sons, pp. 428-431.
+
+
+Data: 1 Response Variable (y = energy)
+ 1 Predictor Variable (x = temperature)
+ 6 Observations
+ Lower Level of Difficulty
+ Observed Data
+
+Model: Miscellaneous Class
+ 2 Parameters (b1 and b2)
+
+ y = b1*x**b2 + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 1 0.7 7.6886226176E-01 1.8281973860E-02
+ b2 = 5 4 3.8604055871E+00 5.1726610913E-02
+
+Residual Sum of Squares: 4.3173084083E-03
+Residual Standard Deviation: 3.2853114039E-02
+Degrees of Freedom: 4
+Number of Observations: 6
+
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 2.138E0 1.309E0
+ 3.421E0 1.471E0
+ 3.597E0 1.490E0
+ 4.340E0 1.565E0
+ 4.882E0 1.611E0
+ 5.660E0 1.680E0
diff --git a/data/nist/ENSO.dat b/data/nist/ENSO.dat
new file mode 100644
index 0000000..f374db2
--- /dev/null
+++ b/data/nist/ENSO.dat
@@ -0,0 +1,228 @@
+NIST/ITL StRD
+Dataset Name: ENSO (ENSO.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 49)
+ Certified Values (lines 41 to 54)
+ Data (lines 61 to 228)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: The data are monthly averaged atmospheric pressure
+ differences between Easter Island and Darwin,
+ Australia. This difference drives the trade winds in
+ the southern hemisphere. Fourier analysis of the data
+ reveals 3 significant cycles. The annual cycle is the
+ strongest, but cycles with periods of approximately 44
+ and 26 months are also present. These cycles
+ correspond to the El Nino and the Southern Oscillation.
+ Arguments to the SIN and COS functions are in radians.
+
+Reference: Kahaner, D., C. Moler, and S. Nash, (1989).
+ Numerical Methods and Software.
+ Englewood Cliffs, NJ: Prentice Hall, pp. 441-445.
+
+Data: 1 Response (y = atmospheric pressure)
+ 1 Predictor (x = time)
+ 168 Observations
+ Average Level of Difficulty
+ Observed Data
+
+Model: Miscellaneous Class
+ 9 Parameters (b1 to b9)
+
+ y = b1 + b2*cos( 2*pi*x/12 ) + b3*sin( 2*pi*x/12 )
+ + b5*cos( 2*pi*x/b4 ) + b6*sin( 2*pi*x/b4 )
+ + b8*cos( 2*pi*x/b7 ) + b9*sin( 2*pi*x/b7 ) + e
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 11.0 10.0 1.0510749193E+01 1.7488832467E-01
+ b2 = 3.0 3.0 3.0762128085E+00 2.4310052139E-01
+ b3 = 0.5 0.5 5.3280138227E-01 2.4354686618E-01
+ b4 = 40.0 44.0 4.4311088700E+01 9.4408025976E-01
+ b5 = -0.7 -1.5 -1.6231428586E+00 2.8078369611E-01
+ b6 = -1.3 0.5 5.2554493756E-01 4.8073701119E-01
+ b7 = 25.0 26.0 2.6887614440E+01 4.1612939130E-01
+ b8 = -0.3 -0.1 2.1232288488E-01 5.1460022911E-01
+ b9 = 1.4 1.5 1.4966870418E+00 2.5434468893E-01
+
+Residual Sum of Squares: 7.8853978668E+02
+Residual Standard Deviation: 2.2269642403E+00
+Degrees of Freedom: 159
+Number of Observations: 168
+
+
+
+
+
+Data: y x
+ 12.90000 1.000000
+ 11.30000 2.000000
+ 10.60000 3.000000
+ 11.20000 4.000000
+ 10.90000 5.000000
+ 7.500000 6.000000
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diff --git a/data/nist/Eckerle4.dat b/data/nist/Eckerle4.dat
new file mode 100644
index 0000000..2d0d8bf
--- /dev/null
+++ b/data/nist/Eckerle4.dat
@@ -0,0 +1,95 @@
+NIST/ITL StRD
+Dataset Name: Eckerle4 (Eckerle4.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 43)
+ Certified Values (lines 41 to 48)
+ Data (lines 61 to 95)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ circular interference transmittance. The response
+ variable is transmittance, and the predictor variable
+ is wavelength.
+
+
+Reference: Eckerle, K., NIST (197?).
+ Circular Interference Transmittance Study.
+
+
+
+
+
+
+Data: 1 Response Variable (y = transmittance)
+ 1 Predictor Variable (x = wavelength)
+ 35 Observations
+ Higher Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 3 Parameters (b1 to b3)
+
+ y = (b1/b2) * exp[-0.5*((x-b3)/b2)**2] + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 1 1.5 1.5543827178E+00 1.5408051163E-02
+ b2 = 10 5 4.0888321754E+00 4.6803020753E-02
+ b3 = 500 450 4.5154121844E+02 4.6800518816E-02
+
+Residual Sum of Squares: 1.4635887487E-03
+Residual Standard Deviation: 6.7629245447E-03
+Degrees of Freedom: 32
+Number of Observations: 35
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 0.0001575E0 400.000000E0
+ 0.0001699E0 405.000000E0
+ 0.0002350E0 410.000000E0
+ 0.0003102E0 415.000000E0
+ 0.0004917E0 420.000000E0
+ 0.0008710E0 425.000000E0
+ 0.0017418E0 430.000000E0
+ 0.0046400E0 435.000000E0
+ 0.0065895E0 436.500000E0
+ 0.0097302E0 438.000000E0
+ 0.0149002E0 439.500000E0
+ 0.0237310E0 441.000000E0
+ 0.0401683E0 442.500000E0
+ 0.0712559E0 444.000000E0
+ 0.1264458E0 445.500000E0
+ 0.2073413E0 447.000000E0
+ 0.2902366E0 448.500000E0
+ 0.3445623E0 450.000000E0
+ 0.3698049E0 451.500000E0
+ 0.3668534E0 453.000000E0
+ 0.3106727E0 454.500000E0
+ 0.2078154E0 456.000000E0
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+ 0.0616764E0 459.000000E0
+ 0.0337200E0 460.500000E0
+ 0.0194023E0 462.000000E0
+ 0.0117831E0 463.500000E0
+ 0.0074357E0 465.000000E0
+ 0.0022732E0 470.000000E0
+ 0.0008800E0 475.000000E0
+ 0.0004579E0 480.000000E0
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+ 0.0001586E0 490.000000E0
+ 0.0001143E0 495.000000E0
+ 0.0000710E0 500.000000E0
diff --git a/data/nist/Gauss1.dat b/data/nist/Gauss1.dat
new file mode 100644
index 0000000..df8dfac
--- /dev/null
+++ b/data/nist/Gauss1.dat
@@ -0,0 +1,310 @@
+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
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diff --git a/data/nist/Gauss2.dat b/data/nist/Gauss2.dat
new file mode 100644
index 0000000..38222eb
--- /dev/null
+++ b/data/nist/Gauss2.dat
@@ -0,0 +1,310 @@
+NIST/ITL StRD
+Dataset Name: Gauss2 (Gauss2.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 slightly-blended 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 = 96.0 98.0 9.9018328406E+01 5.3748766879E-01
+ b2 = 0.009 0.0105 1.0994945399E-02 1.3335306766E-04
+ b3 = 103.0 103.0 1.0188022528E+02 5.9217315772E-01
+ b4 = 106.0 105.0 1.0703095519E+02 1.5006798316E-01
+ b5 = 18.0 20.0 2.3578584029E+01 2.2695595067E-01
+ b6 = 72.0 73.0 7.2045589471E+01 6.1721965884E-01
+ b7 = 151.0 150.0 1.5327010194E+02 1.9466674341E-01
+ b8 = 18.0 20.0 1.9525972636E+01 2.6416549393E-01
+
+Residual Sum of Squares: 1.2475282092E+03
+Residual Standard Deviation: 2.2704790782E+00
+Degrees of Freedom: 242
+Number of Observations: 250
+
+
+
+
+
+
+Data: y x
+ 97.58776 1.000000
+ 97.76344 2.000000
+ 96.56705 3.000000
+ 92.52037 4.000000
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+ 95.21728 6.000000
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diff --git a/data/nist/Gauss3.dat b/data/nist/Gauss3.dat
new file mode 100644
index 0000000..e5eb56d
--- /dev/null
+++ b/data/nist/Gauss3.dat
@@ -0,0 +1,310 @@
+NIST/ITL StRD
+Dataset Name: Gauss3 (Gauss3.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 strongly-blended 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
+ Average 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 = 94.9 96.0 9.8940368970E+01 5.3005192833E-01
+ b2 = 0.009 0.0096 1.0945879335E-02 1.2554058911E-04
+ b3 = 90.1 80.0 1.0069553078E+02 8.1256587317E-01
+ b4 = 113.0 110.0 1.1163619459E+02 3.5317859757E-01
+ b5 = 20.0 25.0 2.3300500029E+01 3.6584783023E-01
+ b6 = 73.8 74.0 7.3705031418E+01 1.2091239082E+00
+ b7 = 140.0 139.0 1.4776164251E+02 4.0488183351E-01
+ b8 = 20.0 25.0 1.9668221230E+01 3.7806634336E-01
+
+Residual Sum of Squares: 1.2444846360E+03
+Residual Standard Deviation: 2.2677077625E+00
+Degrees of Freedom: 242
+Number of Observations: 250
+
+
+
+
+
+
+Data: y x
+ 97.58776 1.000000
+ 97.76344 2.000000
+ 96.56705 3.000000
+ 92.52037 4.000000
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diff --git a/data/nist/Hahn1.dat b/data/nist/Hahn1.dat
new file mode 100644
index 0000000..f3069d7
--- /dev/null
+++ b/data/nist/Hahn1.dat
@@ -0,0 +1,296 @@
+NIST/ITL StRD
+Dataset Name: Hahn1 (Hahn1.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 47)
+ Certified Values (lines 41 to 52)
+ Data (lines 61 to 296)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ the thermal expansion of copper. The response
+ variable is the coefficient of thermal expansion, and
+ the predictor variable is temperature in degrees
+ kelvin.
+
+
+Reference: Hahn, T., NIST (197?).
+ Copper Thermal Expansion Study.
+
+
+
+
+
+Data: 1 Response (y = coefficient of thermal expansion)
+ 1 Predictor (x = temperature, degrees kelvin)
+ 236 Observations
+ Average Level of Difficulty
+ Observed Data
+
+Model: Rational Class (cubic/cubic)
+ 7 Parameters (b1 to b7)
+
+ y = (b1+b2*x+b3*x**2+b4*x**3) /
+ (1+b5*x+b6*x**2+b7*x**3) + e
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 10 1 1.0776351733E+00 1.7070154742E-01
+ b2 = -1 -0.1 -1.2269296921E-01 1.2000289189E-02
+ b3 = 0.05 0.005 4.0863750610E-03 2.2508314937E-04
+ b4 = -0.00001 -0.000001 -1.4262662514E-06 2.7578037666E-07
+ b5 = -0.05 -0.005 -5.7609940901E-03 2.4712888219E-04
+ b6 = 0.001 0.0001 2.4053735503E-04 1.0449373768E-05
+ b7 = -0.000001 -0.0000001 -1.2314450199E-07 1.3027335327E-08
+
+Residual Sum of Squares: 1.5324382854E+00
+Residual Standard Deviation: 8.1803852243E-02
+Degrees of Freedom: 229
+Number of Observations: 236
+
+
+
+
+
+
+
+Data: y x
+ .591E0 24.41E0
+ 1.547E0 34.82E0
+ 2.902E0 44.09E0
+ 2.894E0 45.07E0
+ 4.703E0 54.98E0
+ 6.307E0 65.51E0
+ 7.03E0 70.53E0
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+ 11.615E0 114.26E0
+ 12.005E0 120.25E0
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+ 18.870E0 575.29E0
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+ 19.111E0 625.55E0
+ .367E0 20.15E0
+ .796E0 28.78E0
+ 0.892E0 29.57E0
+ 1.903E0 37.41E0
+ 2.150E0 39.12E0
+ 3.697E0 50.24E0
+ 5.870E0 61.38E0
+ 6.421E0 66.25E0
+ 7.422E0 73.42E0
+ 9.944E0 95.52E0
+ 11.023E0 107.32E0
+ 11.87E0 122.04E0
+ 12.786E0 134.03E0
+ 14.067E0 163.19E0
+ 13.974E0 163.48E0
+ 14.462E0 175.70E0
+ 14.464E0 179.86E0
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+ 16.978E0 339.33E0
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+ 18.486E0 531.08E0
+ 19.090E0 628.34E0
+ 16.062E0 253.24E0
+ 16.337E0 273.13E0
+ 16.345E0 273.66E0
+ 16.388E0 282.10E0
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+ 17.116E0 347.19E0
+ 17.164E0 348.78E0
+ 17.123E0 351.18E0
+ 17.979E0 450.10E0
+ 17.974E0 450.35E0
+ 18.007E0 451.92E0
+ 17.993E0 455.56E0
+ 18.523E0 552.22E0
+ 18.669E0 553.56E0
+ 18.617E0 555.74E0
+ 19.371E0 652.59E0
+ 19.330E0 656.20E0
+ 0.080E0 14.13E0
+ 0.248E0 20.41E0
+ 1.089E0 31.30E0
+ 1.418E0 33.84E0
+ 2.278E0 39.70E0
+ 3.624E0 48.83E0
+ 4.574E0 54.50E0
+ 5.556E0 60.41E0
+ 7.267E0 72.77E0
+ 7.695E0 75.25E0
+ 9.136E0 86.84E0
+ 9.959E0 94.88E0
+ 9.957E0 96.40E0
+ 11.600E0 117.37E0
+ 13.138E0 139.08E0
+ 13.564E0 147.73E0
+ 13.871E0 158.63E0
+ 13.994E0 161.84E0
+ 14.947E0 192.11E0
+ 15.473E0 206.76E0
+ 15.379E0 209.07E0
+ 15.455E0 213.32E0
+ 15.908E0 226.44E0
+ 16.114E0 237.12E0
+ 17.071E0 330.90E0
+ 17.135E0 358.72E0
+ 17.282E0 370.77E0
+ 17.368E0 372.72E0
+ 17.483E0 396.24E0
+ 17.764E0 416.59E0
+ 18.185E0 484.02E0
+ 18.271E0 495.47E0
+ 18.236E0 514.78E0
+ 18.237E0 515.65E0
+ 18.523E0 519.47E0
+ 18.627E0 544.47E0
+ 18.665E0 560.11E0
+ 19.086E0 620.77E0
+ 0.214E0 18.97E0
+ 0.943E0 28.93E0
+ 1.429E0 33.91E0
+ 2.241E0 40.03E0
+ 2.951E0 44.66E0
+ 3.782E0 49.87E0
+ 4.757E0 55.16E0
+ 5.602E0 60.90E0
+ 7.169E0 72.08E0
+ 8.920E0 85.15E0
+ 10.055E0 97.06E0
+ 12.035E0 119.63E0
+ 12.861E0 133.27E0
+ 13.436E0 143.84E0
+ 14.167E0 161.91E0
+ 14.755E0 180.67E0
+ 15.168E0 198.44E0
+ 15.651E0 226.86E0
+ 15.746E0 229.65E0
+ 16.216E0 258.27E0
+ 16.445E0 273.77E0
+ 16.965E0 339.15E0
+ 17.121E0 350.13E0
+ 17.206E0 362.75E0
+ 17.250E0 371.03E0
+ 17.339E0 393.32E0
+ 17.793E0 448.53E0
+ 18.123E0 473.78E0
+ 18.49E0 511.12E0
+ 18.566E0 524.70E0
+ 18.645E0 548.75E0
+ 18.706E0 551.64E0
+ 18.924E0 574.02E0
+ 19.1E0 623.86E0
+ 0.375E0 21.46E0
+ 0.471E0 24.33E0
+ 1.504E0 33.43E0
+ 2.204E0 39.22E0
+ 2.813E0 44.18E0
+ 4.765E0 55.02E0
+ 9.835E0 94.33E0
+ 10.040E0 96.44E0
+ 11.946E0 118.82E0
+ 12.596E0 128.48E0
+ 13.303E0 141.94E0
+ 13.922E0 156.92E0
+ 14.440E0 171.65E0
+ 14.951E0 190.00E0
+ 15.627E0 223.26E0
+ 15.639E0 223.88E0
+ 15.814E0 231.50E0
+ 16.315E0 265.05E0
+ 16.334E0 269.44E0
+ 16.430E0 271.78E0
+ 16.423E0 273.46E0
+ 17.024E0 334.61E0
+ 17.009E0 339.79E0
+ 17.165E0 349.52E0
+ 17.134E0 358.18E0
+ 17.349E0 377.98E0
+ 17.576E0 394.77E0
+ 17.848E0 429.66E0
+ 18.090E0 468.22E0
+ 18.276E0 487.27E0
+ 18.404E0 519.54E0
+ 18.519E0 523.03E0
+ 19.133E0 612.99E0
+ 19.074E0 638.59E0
+ 19.239E0 641.36E0
+ 19.280E0 622.05E0
+ 19.101E0 631.50E0
+ 19.398E0 663.97E0
+ 19.252E0 646.9E0
+ 19.89E0 748.29E0
+ 20.007E0 749.21E0
+ 19.929E0 750.14E0
+ 19.268E0 647.04E0
+ 19.324E0 646.89E0
+ 20.049E0 746.9E0
+ 20.107E0 748.43E0
+ 20.062E0 747.35E0
+ 20.065E0 749.27E0
+ 19.286E0 647.61E0
+ 19.972E0 747.78E0
+ 20.088E0 750.51E0
+ 20.743E0 851.37E0
+ 20.83E0 845.97E0
+ 20.935E0 847.54E0
+ 21.035E0 849.93E0
+ 20.93E0 851.61E0
+ 21.074E0 849.75E0
+ 21.085E0 850.98E0
+ 20.935E0 848.23E0
diff --git a/data/nist/Kirby2.dat b/data/nist/Kirby2.dat
new file mode 100644
index 0000000..04df176
--- /dev/null
+++ b/data/nist/Kirby2.dat
@@ -0,0 +1,211 @@
+NIST/ITL StRD
+Dataset Name: Kirby2 (Kirby2.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 45)
+ Certified Values (lines 41 to 50)
+ Data (lines 61 to 211)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ scanning electron microscope line with standards.
+
+
+Reference: Kirby, R., NIST (197?).
+ Scanning electron microscope line width standards.
+
+
+
+
+
+
+
+
+Data: 1 Response (y)
+ 1 Predictor (x)
+ 151 Observations
+ Average Level of Difficulty
+ Observed Data
+
+Model: Rational Class (quadratic/quadratic)
+ 5 Parameters (b1 to b5)
+
+ y = (b1 + b2*x + b3*x**2) /
+ (1 + b4*x + b5*x**2) + e
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 2 1.5 1.6745063063E+00 8.7989634338E-02
+ b2 = -0.1 -0.15 -1.3927397867E-01 4.1182041386E-03
+ b3 = 0.003 0.0025 2.5961181191E-03 4.1856520458E-05
+ b4 = -0.001 -0.0015 -1.7241811870E-03 5.8931897355E-05
+ b5 = 0.00001 0.00002 2.1664802578E-05 2.0129761919E-07
+
+Residual Sum of Squares: 3.9050739624E+00
+Residual Standard Deviation: 1.6354535131E-01
+Degrees of Freedom: 146
+Number of Observations: 151
+
+
+
+
+
+
+
+
+
+Data: y x
+ 0.0082E0 9.65E0
+ 0.0112E0 10.74E0
+ 0.0149E0 11.81E0
+ 0.0198E0 12.88E0
+ 0.0248E0 14.06E0
+ 0.0324E0 15.28E0
+ 0.0420E0 16.63E0
+ 0.0549E0 18.19E0
+ 0.0719E0 19.88E0
+ 0.0963E0 21.84E0
+ 0.1291E0 24.00E0
+ 0.1710E0 26.25E0
+ 0.2314E0 28.86E0
+ 0.3227E0 31.85E0
+ 0.4809E0 35.79E0
+ 0.7084E0 40.18E0
+ 1.0220E0 44.74E0
+ 1.4580E0 49.53E0
+ 1.9520E0 53.94E0
+ 2.5410E0 58.29E0
+ 3.2230E0 62.63E0
+ 3.9990E0 67.03E0
+ 4.8520E0 71.25E0
+ 5.7320E0 75.22E0
+ 6.7270E0 79.33E0
+ 7.8350E0 83.56E0
+ 9.0250E0 87.75E0
+ 10.2670E0 91.93E0
+ 11.5780E0 96.10E0
+ 12.9440E0 100.28E0
+ 14.3770E0 104.46E0
+ 15.8560E0 108.66E0
+ 17.3310E0 112.71E0
+ 18.8850E0 116.88E0
+ 20.5750E0 121.33E0
+ 22.3200E0 125.79E0
+ 22.3030E0 125.79E0
+ 23.4600E0 128.74E0
+ 24.0600E0 130.27E0
+ 25.2720E0 133.33E0
+ 25.8530E0 134.79E0
+ 27.1100E0 137.93E0
+ 27.6580E0 139.33E0
+ 28.9240E0 142.46E0
+ 29.5110E0 143.90E0
+ 30.7100E0 146.91E0
+ 31.3500E0 148.51E0
+ 32.5200E0 151.41E0
+ 33.2300E0 153.17E0
+ 34.3300E0 155.97E0
+ 35.0600E0 157.76E0
+ 36.1700E0 160.56E0
+ 36.8400E0 162.30E0
+ 38.0100E0 165.21E0
+ 38.6700E0 166.90E0
+ 39.8700E0 169.92E0
+ 40.0300E0 170.32E0
+ 40.5000E0 171.54E0
+ 41.3700E0 173.79E0
+ 41.6700E0 174.57E0
+ 42.3100E0 176.25E0
+ 42.7300E0 177.34E0
+ 43.4600E0 179.19E0
+ 44.1400E0 181.02E0
+ 44.5500E0 182.08E0
+ 45.2200E0 183.88E0
+ 45.9200E0 185.75E0
+ 46.3000E0 186.80E0
+ 47.0000E0 188.63E0
+ 47.6800E0 190.45E0
+ 48.0600E0 191.48E0
+ 48.7400E0 193.35E0
+ 49.4100E0 195.22E0
+ 49.7600E0 196.23E0
+ 50.4300E0 198.05E0
+ 51.1100E0 199.97E0
+ 51.5000E0 201.06E0
+ 52.1200E0 202.83E0
+ 52.7600E0 204.69E0
+ 53.1800E0 205.86E0
+ 53.7800E0 207.58E0
+ 54.4600E0 209.50E0
+ 54.8300E0 210.65E0
+ 55.4000E0 212.33E0
+ 56.4300E0 215.43E0
+ 57.0300E0 217.16E0
+ 58.0000E0 220.21E0
+ 58.6100E0 221.98E0
+ 59.5800E0 225.06E0
+ 60.1100E0 226.79E0
+ 61.1000E0 229.92E0
+ 61.6500E0 231.69E0
+ 62.5900E0 234.77E0
+ 63.1200E0 236.60E0
+ 64.0300E0 239.63E0
+ 64.6200E0 241.50E0
+ 65.4900E0 244.48E0
+ 66.0300E0 246.40E0
+ 66.8900E0 249.35E0
+ 67.4200E0 251.32E0
+ 68.2300E0 254.22E0
+ 68.7700E0 256.24E0
+ 69.5900E0 259.11E0
+ 70.1100E0 261.18E0
+ 70.8600E0 264.02E0
+ 71.4300E0 266.13E0
+ 72.1600E0 268.94E0
+ 72.7000E0 271.09E0
+ 73.4000E0 273.87E0
+ 73.9300E0 276.08E0
+ 74.6000E0 278.83E0
+ 75.1600E0 281.08E0
+ 75.8200E0 283.81E0
+ 76.3400E0 286.11E0
+ 76.9800E0 288.81E0
+ 77.4800E0 291.08E0
+ 78.0800E0 293.75E0
+ 78.6000E0 295.99E0
+ 79.1700E0 298.64E0
+ 79.6200E0 300.84E0
+ 79.8800E0 302.02E0
+ 80.1900E0 303.48E0
+ 80.6600E0 305.65E0
+ 81.2200E0 308.27E0
+ 81.6600E0 310.41E0
+ 82.1600E0 313.01E0
+ 82.5900E0 315.12E0
+ 83.1400E0 317.71E0
+ 83.5000E0 319.79E0
+ 84.0000E0 322.36E0
+ 84.4000E0 324.42E0
+ 84.8900E0 326.98E0
+ 85.2600E0 329.01E0
+ 85.7400E0 331.56E0
+ 86.0700E0 333.56E0
+ 86.5400E0 336.10E0
+ 86.8900E0 338.08E0
+ 87.3200E0 340.60E0
+ 87.6500E0 342.57E0
+ 88.1000E0 345.08E0
+ 88.4300E0 347.02E0
+ 88.8300E0 349.52E0
+ 89.1200E0 351.44E0
+ 89.5400E0 353.93E0
+ 89.8500E0 355.83E0
+ 90.2500E0 358.32E0
+ 90.5500E0 360.20E0
+ 90.9300E0 362.67E0
+ 91.2000E0 364.53E0
+ 91.5500E0 367.00E0
+ 92.2000E0 371.30E0
diff --git a/data/nist/Lanczos1.dat b/data/nist/Lanczos1.dat
new file mode 100644
index 0000000..8107320
--- /dev/null
+++ b/data/nist/Lanczos1.dat
@@ -0,0 +1,84 @@
+NIST/ITL StRD
+Dataset Name: Lanczos1 (Lanczos1.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 46)
+ Certified Values (lines 41 to 51)
+ Data (lines 61 to 84)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are taken from an example discussed in
+ Lanczos (1956). The data were generated to 14-digits
+ of accuracy using
+ f(x) = 0.0951*exp(-x) + 0.8607*exp(-3*x)
+ + 1.5576*exp(-5*x).
+
+
+Reference: Lanczos, C. (1956).
+ Applied Analysis.
+ Englewood Cliffs, NJ: Prentice Hall, pp. 272-280.
+
+
+
+
+Data: 1 Response (y)
+ 1 Predictor (x)
+ 24 Observations
+ Average Level of Difficulty
+ Generated Data
+
+Model: Exponential Class
+ 6 Parameters (b1 to b6)
+
+ y = b1*exp(-b2*x) + b3*exp(-b4*x) + b5*exp(-b6*x) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 1.2 0.5 9.5100000027E-02 5.3347304234E-11
+ b2 = 0.3 0.7 1.0000000001E+00 2.7473038179E-10
+ b3 = 5.6 3.6 8.6070000013E-01 1.3576062225E-10
+ b4 = 5.5 4.2 3.0000000002E+00 3.3308253069E-10
+ b5 = 6.5 4 1.5575999998E+00 1.8815731448E-10
+ b6 = 7.6 6.3 5.0000000001E+00 1.1057500538E-10
+
+Residual Sum of Squares: 1.4307867721E-25
+Residual Standard Deviation: 8.9156129349E-14
+Degrees of Freedom: 18
+Number of Observations: 24
+
+
+
+
+
+
+
+
+Data: y x
+ 2.513400000000E+00 0.000000000000E+00
+ 2.044333373291E+00 5.000000000000E-02
+ 1.668404436564E+00 1.000000000000E-01
+ 1.366418021208E+00 1.500000000000E-01
+ 1.123232487372E+00 2.000000000000E-01
+ 9.268897180037E-01 2.500000000000E-01
+ 7.679338563728E-01 3.000000000000E-01
+ 6.388775523106E-01 3.500000000000E-01
+ 5.337835317402E-01 4.000000000000E-01
+ 4.479363617347E-01 4.500000000000E-01
+ 3.775847884350E-01 5.000000000000E-01
+ 3.197393199326E-01 5.500000000000E-01
+ 2.720130773746E-01 6.000000000000E-01
+ 2.324965529032E-01 6.500000000000E-01
+ 1.996589546065E-01 7.000000000000E-01
+ 1.722704126914E-01 7.500000000000E-01
+ 1.493405660168E-01 8.000000000000E-01
+ 1.300700206922E-01 8.500000000000E-01
+ 1.138119324644E-01 9.000000000000E-01
+ 1.000415587559E-01 9.500000000000E-01
+ 8.833209084540E-02 1.000000000000E+00
+ 7.833544019350E-02 1.050000000000E+00
+ 6.976693743449E-02 1.100000000000E+00
+ 6.239312536719E-02 1.150000000000E+00
diff --git a/data/nist/Lanczos2.dat b/data/nist/Lanczos2.dat
new file mode 100644
index 0000000..fc98e69
--- /dev/null
+++ b/data/nist/Lanczos2.dat
@@ -0,0 +1,84 @@
+NIST/ITL StRD
+Dataset Name: Lanczos2 (Lanczos2.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 46)
+ Certified Values (lines 41 to 51)
+ Data (lines 61 to 84)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are taken from an example discussed in
+ Lanczos (1956). The data were generated to 6-digits
+ of accuracy using
+ f(x) = 0.0951*exp(-x) + 0.8607*exp(-3*x)
+ + 1.5576*exp(-5*x).
+
+
+Reference: Lanczos, C. (1956).
+ Applied Analysis.
+ Englewood Cliffs, NJ: Prentice Hall, pp. 272-280.
+
+
+
+
+Data: 1 Response (y)
+ 1 Predictor (x)
+ 24 Observations
+ Average Level of Difficulty
+ Generated Data
+
+Model: Exponential Class
+ 6 Parameters (b1 to b6)
+
+ y = b1*exp(-b2*x) + b3*exp(-b4*x) + b5*exp(-b6*x) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 1.2 0.5 9.6251029939E-02 6.6770575477E-04
+ b2 = 0.3 0.7 1.0057332849E+00 3.3989646176E-03
+ b3 = 5.6 3.6 8.6424689056E-01 1.7185846685E-03
+ b4 = 5.5 4.2 3.0078283915E+00 4.1707005856E-03
+ b5 = 6.5 4 1.5529016879E+00 2.3744381417E-03
+ b6 = 7.6 6.3 5.0028798100E+00 1.3958787284E-03
+
+Residual Sum of Squares: 2.2299428125E-11
+Residual Standard Deviation: 1.1130395851E-06
+Degrees of Freedom: 18
+Number of Observations: 24
+
+
+
+
+
+
+
+
+Data: y x
+ 2.51340E+00 0.00000E+00
+ 2.04433E+00 5.00000E-02
+ 1.66840E+00 1.00000E-01
+ 1.36642E+00 1.50000E-01
+ 1.12323E+00 2.00000E-01
+ 9.26890E-01 2.50000E-01
+ 7.67934E-01 3.00000E-01
+ 6.38878E-01 3.50000E-01
+ 5.33784E-01 4.00000E-01
+ 4.47936E-01 4.50000E-01
+ 3.77585E-01 5.00000E-01
+ 3.19739E-01 5.50000E-01
+ 2.72013E-01 6.00000E-01
+ 2.32497E-01 6.50000E-01
+ 1.99659E-01 7.00000E-01
+ 1.72270E-01 7.50000E-01
+ 1.49341E-01 8.00000E-01
+ 1.30070E-01 8.50000E-01
+ 1.13812E-01 9.00000E-01
+ 1.00042E-01 9.50000E-01
+ 8.83321E-02 1.00000E+00
+ 7.83354E-02 1.05000E+00
+ 6.97669E-02 1.10000E+00
+ 6.23931E-02 1.15000E+00
diff --git a/data/nist/Lanczos3.dat b/data/nist/Lanczos3.dat
new file mode 100644
index 0000000..d930d65
--- /dev/null
+++ b/data/nist/Lanczos3.dat
@@ -0,0 +1,84 @@
+NIST/ITL StRD
+Dataset Name: Lanczos3 (Lanczos3.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 46)
+ Certified Values (lines 41 to 51)
+ Data (lines 61 to 84)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are taken from an example discussed in
+ Lanczos (1956). The data were generated to 5-digits
+ of accuracy using
+ f(x) = 0.0951*exp(-x) + 0.8607*exp(-3*x)
+ + 1.5576*exp(-5*x).
+
+
+Reference: Lanczos, C. (1956).
+ Applied Analysis.
+ Englewood Cliffs, NJ: Prentice Hall, pp. 272-280.
+
+
+
+
+Data: 1 Response (y)
+ 1 Predictor (x)
+ 24 Observations
+ Lower Level of Difficulty
+ Generated Data
+
+Model: Exponential Class
+ 6 Parameters (b1 to b6)
+
+ y = b1*exp(-b2*x) + b3*exp(-b4*x) + b5*exp(-b6*x) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 1.2 0.5 8.6816414977E-02 1.7197908859E-02
+ b2 = 0.3 0.7 9.5498101505E-01 9.7041624475E-02
+ b3 = 5.6 3.6 8.4400777463E-01 4.1488663282E-02
+ b4 = 5.5 4.2 2.9515951832E+00 1.0766312506E-01
+ b5 = 6.5 4 1.5825685901E+00 5.8371576281E-02
+ b6 = 7.6 6.3 4.9863565084E+00 3.4436403035E-02
+
+Residual Sum of Squares: 1.6117193594E-08
+Residual Standard Deviation: 2.9923229172E-05
+Degrees of Freedom: 18
+Number of Observations: 24
+
+
+
+
+
+
+
+
+Data: y x
+ 2.5134E+00 0.00000E+00
+ 2.0443E+00 5.00000E-02
+ 1.6684E+00 1.00000E-01
+ 1.3664E+00 1.50000E-01
+ 1.1232E+00 2.00000E-01
+ 0.9269E+00 2.50000E-01
+ 0.7679E+00 3.00000E-01
+ 0.6389E+00 3.50000E-01
+ 0.5338E+00 4.00000E-01
+ 0.4479E+00 4.50000E-01
+ 0.3776E+00 5.00000E-01
+ 0.3197E+00 5.50000E-01
+ 0.2720E+00 6.00000E-01
+ 0.2325E+00 6.50000E-01
+ 0.1997E+00 7.00000E-01
+ 0.1723E+00 7.50000E-01
+ 0.1493E+00 8.00000E-01
+ 0.1301E+00 8.50000E-01
+ 0.1138E+00 9.00000E-01
+ 0.1000E+00 9.50000E-01
+ 0.0883E+00 1.00000E+00
+ 0.0783E+00 1.05000E+00
+ 0.0698E+00 1.10000E+00
+ 0.0624E+00 1.15000E+00
diff --git a/data/nist/MGH09.dat b/data/nist/MGH09.dat
new file mode 100644
index 0000000..1f19af8
--- /dev/null
+++ b/data/nist/MGH09.dat
@@ -0,0 +1,71 @@
+NIST/ITL StRD
+Dataset Name: MGH09 (MGH09.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 44)
+ Certified Values (lines 41 to 49)
+ Data (lines 61 to 71)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: This problem was found to be difficult for some very
+ good algorithms. There is a local minimum at (+inf,
+ -14.07..., -inf, -inf) with final sum of squares
+ 0.00102734....
+
+ 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: Kowalik, J.S., and M. R. Osborne, (1978).
+ Methods for Unconstrained Optimization Problems.
+ New York, NY: Elsevier North-Holland.
+
+Data: 1 Response (y)
+ 1 Predictor (x)
+ 11 Observations
+ Higher Level of Difficulty
+ Generated Data
+
+Model: Rational Class (linear/quadratic)
+ 4 Parameters (b1 to b4)
+
+ y = b1*(x**2+x*b2) / (x**2+x*b3+b4) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 25 0.25 1.9280693458E-01 1.1435312227E-02
+ b2 = 39 0.39 1.9128232873E-01 1.9633220911E-01
+ b3 = 41.5 0.415 1.2305650693E-01 8.0842031232E-02
+ b4 = 39 0.39 1.3606233068E-01 9.0025542308E-02
+
+Residual Sum of Squares: 3.0750560385E-04
+Residual Standard Deviation: 6.6279236551E-03
+Degrees of Freedom: 7
+Number of Observations: 11
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 1.957000E-01 4.000000E+00
+ 1.947000E-01 2.000000E+00
+ 1.735000E-01 1.000000E+00
+ 1.600000E-01 5.000000E-01
+ 8.440000E-02 2.500000E-01
+ 6.270000E-02 1.670000E-01
+ 4.560000E-02 1.250000E-01
+ 3.420000E-02 1.000000E-01
+ 3.230000E-02 8.330000E-02
+ 2.350000E-02 7.140000E-02
+ 2.460000E-02 6.250000E-02
diff --git a/data/nist/MGH10.dat b/data/nist/MGH10.dat
new file mode 100644
index 0000000..df88ea4
--- /dev/null
+++ b/data/nist/MGH10.dat
@@ -0,0 +1,76 @@
+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
diff --git a/data/nist/MGH17.dat b/data/nist/MGH17.dat
new file mode 100644
index 0000000..3b3b7e8
--- /dev/null
+++ b/data/nist/MGH17.dat
@@ -0,0 +1,93 @@
+NIST/ITL StRD
+Dataset Name: MGH17 (MGH17.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 45)
+ Certified Values (lines 41 to 50)
+ Data (lines 61 to 93)
+
+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: Osborne, M. R. (1972).
+ Some aspects of nonlinear least squares
+ calculations. In Numerical Methods for Nonlinear
+ Optimization, Lootsma (Ed).
+ New York, NY: Academic Press, pp. 171-189.
+
+Data: 1 Response (y)
+ 1 Predictor (x)
+ 33 Observations
+ Average Level of Difficulty
+ Generated Data
+
+Model: Exponential Class
+ 5 Parameters (b1 to b5)
+
+ y = b1 + b2*exp[-x*b4] + b3*exp[-x*b5] + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 50 0.5 3.7541005211E-01 2.0723153551E-03
+ b2 = 150 1.5 1.9358469127E+00 2.2031669222E-01
+ b3 = -100 -1 -1.4646871366E+00 2.2175707739E-01
+ b4 = 1 0.01 1.2867534640E-02 4.4861358114E-04
+ b5 = 2 0.02 2.2122699662E-02 8.9471996575E-04
+
+Residual Sum of Squares: 5.4648946975E-05
+Residual Standard Deviation: 1.3970497866E-03
+Degrees of Freedom: 28
+Number of Observations: 33
+
+
+
+
+
+
+
+
+
+Data: y x
+ 8.440000E-01 0.000000E+00
+ 9.080000E-01 1.000000E+01
+ 9.320000E-01 2.000000E+01
+ 9.360000E-01 3.000000E+01
+ 9.250000E-01 4.000000E+01
+ 9.080000E-01 5.000000E+01
+ 8.810000E-01 6.000000E+01
+ 8.500000E-01 7.000000E+01
+ 8.180000E-01 8.000000E+01
+ 7.840000E-01 9.000000E+01
+ 7.510000E-01 1.000000E+02
+ 7.180000E-01 1.100000E+02
+ 6.850000E-01 1.200000E+02
+ 6.580000E-01 1.300000E+02
+ 6.280000E-01 1.400000E+02
+ 6.030000E-01 1.500000E+02
+ 5.800000E-01 1.600000E+02
+ 5.580000E-01 1.700000E+02
+ 5.380000E-01 1.800000E+02
+ 5.220000E-01 1.900000E+02
+ 5.060000E-01 2.000000E+02
+ 4.900000E-01 2.100000E+02
+ 4.780000E-01 2.200000E+02
+ 4.670000E-01 2.300000E+02
+ 4.570000E-01 2.400000E+02
+ 4.480000E-01 2.500000E+02
+ 4.380000E-01 2.600000E+02
+ 4.310000E-01 2.700000E+02
+ 4.240000E-01 2.800000E+02
+ 4.200000E-01 2.900000E+02
+ 4.140000E-01 3.000000E+02
+ 4.110000E-01 3.100000E+02
+ 4.060000E-01 3.200000E+02
diff --git a/data/nist/Misra1a.dat b/data/nist/Misra1a.dat
new file mode 100644
index 0000000..332f37e
--- /dev/null
+++ b/data/nist/Misra1a.dat
@@ -0,0 +1,74 @@
+NIST/ITL StRD
+Dataset Name: Misra1a (Misra1a.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 42)
+ Certified Values (lines 41 to 47)
+ Data (lines 61 to 74)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study regarding
+ dental research in monomolecular adsorption. The
+ response variable is volume, and the predictor
+ variable is pressure.
+
+Reference: Misra, D., NIST (1978).
+ Dental Research Monomolecular Adsorption Study.
+
+
+
+
+
+
+
+Data: 1 Response Variable (y = volume)
+ 1 Predictor Variable (x = pressure)
+ 14 Observations
+ Lower Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 2 Parameters (b1 and b2)
+
+ y = b1*(1-exp[-b2*x]) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 500 250 2.3894212918E+02 2.7070075241E+00
+ b2 = 0.0001 0.0005 5.5015643181E-04 7.2668688436E-06
+
+Residual Sum of Squares: 1.2455138894E-01
+Residual Standard Deviation: 1.0187876330E-01
+Degrees of Freedom: 12
+Number of Observations: 14
+
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 10.07E0 77.6E0
+ 14.73E0 114.9E0
+ 17.94E0 141.1E0
+ 23.93E0 190.8E0
+ 29.61E0 239.9E0
+ 35.18E0 289.0E0
+ 40.02E0 332.8E0
+ 44.82E0 378.4E0
+ 50.76E0 434.8E0
+ 55.05E0 477.3E0
+ 61.01E0 536.8E0
+ 66.40E0 593.1E0
+ 75.47E0 689.1E0
+ 81.78E0 760.0E0
diff --git a/data/nist/Misra1b.dat b/data/nist/Misra1b.dat
new file mode 100644
index 0000000..7923d40
--- /dev/null
+++ b/data/nist/Misra1b.dat
@@ -0,0 +1,74 @@
+NIST/ITL StRD
+Dataset Name: Misra1b (Misra1b.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 42)
+ Certified Values (lines 41 to 47)
+ Data (lines 61 to 74)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study regarding
+ dental research in monomolecular adsorption. The
+ response variable is volume, and the predictor
+ variable is pressure.
+
+Reference: Misra, D., NIST (1978).
+ Dental Research Monomolecular Adsorption Study.
+
+
+
+
+
+
+
+Data: 1 Response (y = volume)
+ 1 Predictor (x = pressure)
+ 14 Observations
+ Lower Level of Difficulty
+ Observed Data
+
+Model: Miscellaneous Class
+ 2 Parameters (b1 and b2)
+
+ y = b1 * (1-(1+b2*x/2)**(-2)) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 500 300 3.3799746163E+02 3.1643950207E+00
+ b2 = 0.0001 0.0002 3.9039091287E-04 4.2547321834E-06
+
+Residual Sum of Squares: 7.5464681533E-02
+Residual Standard Deviation: 7.9301471998E-02
+Degrees of Freedom: 12
+Number of Observations: 14
+
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 10.07E0 77.6E0
+ 14.73E0 114.9E0
+ 17.94E0 141.1E0
+ 23.93E0 190.8E0
+ 29.61E0 239.9E0
+ 35.18E0 289.0E0
+ 40.02E0 332.8E0
+ 44.82E0 378.4E0
+ 50.76E0 434.8E0
+ 55.05E0 477.3E0
+ 61.01E0 536.8E0
+ 66.40E0 593.1E0
+ 75.47E0 689.1E0
+ 81.78E0 760.0E0
diff --git a/data/nist/Misra1c.dat b/data/nist/Misra1c.dat
new file mode 100644
index 0000000..d86bc82
--- /dev/null
+++ b/data/nist/Misra1c.dat
@@ -0,0 +1,74 @@
+NIST/ITL StRD
+Dataset Name: Misra1c (Misra1c.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 42)
+ Certified Values (lines 41 to 47)
+ Data (lines 61 to 74)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study regarding
+ dental research in monomolecular adsorption. The
+ response variable is volume, and the predictor
+ variable is pressure.
+
+Reference: Misra, D., NIST (1978).
+ Dental Research Monomolecular Adsorption.
+
+
+
+
+
+
+
+Data: 1 Response (y = volume)
+ 1 Predictor (x = pressure)
+ 14 Observations
+ Average Level of Difficulty
+ Observed Data
+
+Model: Miscellaneous Class
+ 2 Parameters (b1 and b2)
+
+ y = b1 * (1-(1+2*b2*x)**(-.5)) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 500 600 6.3642725809E+02 4.6638326572E+00
+ b2 = 0.0001 0.0002 2.0813627256E-04 1.7728423155E-06
+
+Residual Sum of Squares: 4.0966836971E-02
+Residual Standard Deviation: 5.8428615257E-02
+Degrees of Freedom: 12
+Number of Observations: 14
+
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 10.07E0 77.6E0
+ 14.73E0 114.9E0
+ 17.94E0 141.1E0
+ 23.93E0 190.8E0
+ 29.61E0 239.9E0
+ 35.18E0 289.0E0
+ 40.02E0 332.8E0
+ 44.82E0 378.4E0
+ 50.76E0 434.8E0
+ 55.05E0 477.3E0
+ 61.01E0 536.8E0
+ 66.40E0 593.1E0
+ 75.47E0 689.1E0
+ 81.78E0 760.0E0
diff --git a/data/nist/Misra1d.dat b/data/nist/Misra1d.dat
new file mode 100644
index 0000000..237de46
--- /dev/null
+++ b/data/nist/Misra1d.dat
@@ -0,0 +1,74 @@
+NIST/ITL StRD
+Dataset Name: Misra1d (Misra1d.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 42)
+ Certified Values (lines 41 to 47)
+ Data (lines 61 to 74)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study regarding
+ dental research in monomolecular adsorption. The
+ response variable is volume, and the predictor
+ variable is pressure.
+
+Reference: Misra, D., NIST (1978).
+ Dental Research Monomolecular Adsorption Study.
+
+
+
+
+
+
+
+Data: 1 Response (y = volume)
+ 1 Predictor (x = pressure)
+ 14 Observations
+ Average Level of Difficulty
+ Observed Data
+
+Model: Miscellaneous Class
+ 2 Parameters (b1 and b2)
+
+ y = b1*b2*x*((1+b2*x)**(-1)) + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 500 450 4.3736970754E+02 3.6489174345E+00
+ b2 = 0.0001 0.0003 3.0227324449E-04 2.9334354479E-06
+
+Residual Sum of Squares: 5.6419295283E-02
+Residual Standard Deviation: 6.8568272111E-02
+Degrees of Freedom: 12
+Number of Observations: 14
+
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 10.07E0 77.6E0
+ 14.73E0 114.9E0
+ 17.94E0 141.1E0
+ 23.93E0 190.8E0
+ 29.61E0 239.9E0
+ 35.18E0 289.0E0
+ 40.02E0 332.8E0
+ 44.82E0 378.4E0
+ 50.76E0 434.8E0
+ 55.05E0 477.3E0
+ 61.01E0 536.8E0
+ 66.40E0 593.1E0
+ 75.47E0 689.1E0
+ 81.78E0 760.0E0
diff --git a/data/nist/Nelson.dat b/data/nist/Nelson.dat
new file mode 100644
index 0000000..5ce1003
--- /dev/null
+++ b/data/nist/Nelson.dat
@@ -0,0 +1,188 @@
+NIST/ITL StRD
+Dataset Name: Nelson (Nelson.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 43)
+ Certified Values (lines 41 to 48)
+ Data (lines 61 to 188)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a study involving
+ the analysis of performance degradation data from
+ accelerated tests, published in IEEE Transactions
+ on Reliability. The response variable is dialectric
+ breakdown strength in kilo-volts, and the predictor
+ variables are time in weeks and temperature in degrees
+ Celcius.
+
+
+Reference: Nelson, W. (1981).
+ Analysis of Performance-Degradation Data.
+ IEEE Transactions on Reliability.
+ Vol. 2, R-30, No. 2, pp. 149-155.
+
+Data: 1 Response ( y = dialectric breakdown strength)
+ 2 Predictors (x1 = time; x2 = temperature)
+ 128 Observations
+ Average Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 3 Parameters (b1 to b3)
+
+ log[y] = b1 - b2*x1 * exp[-b3*x2] + e
+
+
+
+ Starting values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 2 2.5 2.5906836021E+00 1.9149996413E-02
+ b2 = 0.0001 0.000000005 5.6177717026E-09 6.1124096540E-09
+ b3 = -0.01 -0.05 -5.7701013174E-02 3.9572366543E-03
+
+Residual Sum of Squares: 3.7976833176E+00
+Residual Standard Deviation: 1.7430280130E-01
+Degrees of Freedom: 125
+Number of Observations: 128
+
+
+
+
+
+
+
+
+
+
+
+Data: y x1 x2
+ 15.00E0 1E0 180E0
+ 17.00E0 1E0 180E0
+ 15.50E0 1E0 180E0
+ 16.50E0 1E0 180E0
+ 15.50E0 1E0 225E0
+ 15.00E0 1E0 225E0
+ 16.00E0 1E0 225E0
+ 14.50E0 1E0 225E0
+ 15.00E0 1E0 250E0
+ 14.50E0 1E0 250E0
+ 12.50E0 1E0 250E0
+ 11.00E0 1E0 250E0
+ 14.00E0 1E0 275E0
+ 13.00E0 1E0 275E0
+ 14.00E0 1E0 275E0
+ 11.50E0 1E0 275E0
+ 14.00E0 2E0 180E0
+ 16.00E0 2E0 180E0
+ 13.00E0 2E0 180E0
+ 13.50E0 2E0 180E0
+ 13.00E0 2E0 225E0
+ 13.50E0 2E0 225E0
+ 12.50E0 2E0 225E0
+ 12.50E0 2E0 225E0
+ 12.50E0 2E0 250E0
+ 12.00E0 2E0 250E0
+ 11.50E0 2E0 250E0
+ 12.00E0 2E0 250E0
+ 13.00E0 2E0 275E0
+ 11.50E0 2E0 275E0
+ 13.00E0 2E0 275E0
+ 12.50E0 2E0 275E0
+ 13.50E0 4E0 180E0
+ 17.50E0 4E0 180E0
+ 17.50E0 4E0 180E0
+ 13.50E0 4E0 180E0
+ 12.50E0 4E0 225E0
+ 12.50E0 4E0 225E0
+ 15.00E0 4E0 225E0
+ 13.00E0 4E0 225E0
+ 12.00E0 4E0 250E0
+ 13.00E0 4E0 250E0
+ 12.00E0 4E0 250E0
+ 13.50E0 4E0 250E0
+ 10.00E0 4E0 275E0
+ 11.50E0 4E0 275E0
+ 11.00E0 4E0 275E0
+ 9.50E0 4E0 275E0
+ 15.00E0 8E0 180E0
+ 15.00E0 8E0 180E0
+ 15.50E0 8E0 180E0
+ 16.00E0 8E0 180E0
+ 13.00E0 8E0 225E0
+ 10.50E0 8E0 225E0
+ 13.50E0 8E0 225E0
+ 14.00E0 8E0 225E0
+ 12.50E0 8E0 250E0
+ 12.00E0 8E0 250E0
+ 11.50E0 8E0 250E0
+ 11.50E0 8E0 250E0
+ 6.50E0 8E0 275E0
+ 5.50E0 8E0 275E0
+ 6.00E0 8E0 275E0
+ 6.00E0 8E0 275E0
+ 18.50E0 16E0 180E0
+ 17.00E0 16E0 180E0
+ 15.30E0 16E0 180E0
+ 16.00E0 16E0 180E0
+ 13.00E0 16E0 225E0
+ 14.00E0 16E0 225E0
+ 12.50E0 16E0 225E0
+ 11.00E0 16E0 225E0
+ 12.00E0 16E0 250E0
+ 12.00E0 16E0 250E0
+ 11.50E0 16E0 250E0
+ 12.00E0 16E0 250E0
+ 6.00E0 16E0 275E0
+ 6.00E0 16E0 275E0
+ 5.00E0 16E0 275E0
+ 5.50E0 16E0 275E0
+ 12.50E0 32E0 180E0
+ 13.00E0 32E0 180E0
+ 16.00E0 32E0 180E0
+ 12.00E0 32E0 180E0
+ 11.00E0 32E0 225E0
+ 9.50E0 32E0 225E0
+ 11.00E0 32E0 225E0
+ 11.00E0 32E0 225E0
+ 11.00E0 32E0 250E0
+ 10.00E0 32E0 250E0
+ 10.50E0 32E0 250E0
+ 10.50E0 32E0 250E0
+ 2.70E0 32E0 275E0
+ 2.70E0 32E0 275E0
+ 2.50E0 32E0 275E0
+ 2.40E0 32E0 275E0
+ 13.00E0 48E0 180E0
+ 13.50E0 48E0 180E0
+ 16.50E0 48E0 180E0
+ 13.60E0 48E0 180E0
+ 11.50E0 48E0 225E0
+ 10.50E0 48E0 225E0
+ 13.50E0 48E0 225E0
+ 12.00E0 48E0 225E0
+ 7.00E0 48E0 250E0
+ 6.90E0 48E0 250E0
+ 8.80E0 48E0 250E0
+ 7.90E0 48E0 250E0
+ 1.20E0 48E0 275E0
+ 1.50E0 48E0 275E0
+ 1.00E0 48E0 275E0
+ 1.50E0 48E0 275E0
+ 13.00E0 64E0 180E0
+ 12.50E0 64E0 180E0
+ 16.50E0 64E0 180E0
+ 16.00E0 64E0 180E0
+ 11.00E0 64E0 225E0
+ 11.50E0 64E0 225E0
+ 10.50E0 64E0 225E0
+ 10.00E0 64E0 225E0
+ 7.27E0 64E0 250E0
+ 7.50E0 64E0 250E0
+ 6.70E0 64E0 250E0
+ 7.60E0 64E0 250E0
+ 1.50E0 64E0 275E0
+ 1.00E0 64E0 275E0
+ 1.20E0 64E0 275E0
+ 1.20E0 64E0 275E0
diff --git a/data/nist/Rat42.dat b/data/nist/Rat42.dat
new file mode 100644
index 0000000..e112fbb
--- /dev/null
+++ b/data/nist/Rat42.dat
@@ -0,0 +1,69 @@
+NIST/ITL StRD
+Dataset Name: Rat42 (Rat42.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 43)
+ Certified Values (lines 41 to 48)
+ Data (lines 61 to 69)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: This model and data are an example of fitting
+ sigmoidal growth curves taken from Ratkowsky (1983).
+ The response variable is pasture yield, and the
+ predictor variable is growing time.
+
+
+Reference: Ratkowsky, D.A. (1983).
+ Nonlinear Regression Modeling.
+ New York, NY: Marcel Dekker, pp. 61 and 88.
+
+
+
+
+
+Data: 1 Response (y = pasture yield)
+ 1 Predictor (x = growing time)
+ 9 Observations
+ Higher Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 3 Parameters (b1 to b3)
+
+ y = b1 / (1+exp[b2-b3*x]) + e
+
+
+
+ Starting Values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 100 75 7.2462237576E+01 1.7340283401E+00
+ b2 = 1 2.5 2.6180768402E+00 8.8295217536E-02
+ b3 = 0.1 0.07 6.7359200066E-02 3.4465663377E-03
+
+Residual Sum of Squares: 8.0565229338E+00
+Residual Standard Deviation: 1.1587725499E+00
+Degrees of Freedom: 6
+Number of Observations: 9
+
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 8.930E0 9.000E0
+ 10.800E0 14.000E0
+ 18.590E0 21.000E0
+ 22.330E0 28.000E0
+ 39.350E0 42.000E0
+ 56.110E0 57.000E0
+ 61.730E0 63.000E0
+ 64.620E0 70.000E0
+ 67.080E0 79.000E0
diff --git a/data/nist/Rat43.dat b/data/nist/Rat43.dat
new file mode 100644
index 0000000..347d846
--- /dev/null
+++ b/data/nist/Rat43.dat
@@ -0,0 +1,75 @@
+NIST/ITL StRD
+Dataset Name: Rat43 (Rat43.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 44)
+ Certified Values (lines 41 to 49)
+ Data (lines 61 to 75)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: This model and data are an example of fitting
+ sigmoidal growth curves taken from Ratkowsky (1983).
+ The response variable is the dry weight of onion bulbs
+ and tops, and the predictor variable is growing time.
+
+
+Reference: Ratkowsky, D.A. (1983).
+ Nonlinear Regression Modeling.
+ New York, NY: Marcel Dekker, pp. 62 and 88.
+
+
+
+
+
+Data: 1 Response (y = onion bulb dry weight)
+ 1 Predictor (x = growing time)
+ 15 Observations
+ Higher Level of Difficulty
+ Observed Data
+
+Model: Exponential Class
+ 4 Parameters (b1 to b4)
+
+ y = b1 / ((1+exp[b2-b3*x])**(1/b4)) + e
+
+
+
+ Starting Values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 100 700 6.9964151270E+02 1.6302297817E+01
+ b2 = 10 5 5.2771253025E+00 2.0828735829E+00
+ b3 = 1 0.75 7.5962938329E-01 1.9566123451E-01
+ b4 = 1 1.3 1.2792483859E+00 6.8761936385E-01
+
+Residual Sum of Squares: 8.7864049080E+03
+Residual Standard Deviation: 2.8262414662E+01
+Degrees of Freedom: 9
+Number of Observations: 15
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 16.08E0 1.0E0
+ 33.83E0 2.0E0
+ 65.80E0 3.0E0
+ 97.20E0 4.0E0
+ 191.55E0 5.0E0
+ 326.20E0 6.0E0
+ 386.87E0 7.0E0
+ 520.53E0 8.0E0
+ 590.03E0 9.0E0
+ 651.92E0 10.0E0
+ 724.93E0 11.0E0
+ 699.56E0 12.0E0
+ 689.96E0 13.0E0
+ 637.56E0 14.0E0
+ 717.41E0 15.0E0
diff --git a/data/nist/Roszman1.dat b/data/nist/Roszman1.dat
new file mode 100644
index 0000000..0296837
--- /dev/null
+++ b/data/nist/Roszman1.dat
@@ -0,0 +1,85 @@
+NIST/ITL StRD
+Dataset Name: Roszman1 (Roszman1.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 44)
+ Certified Values (lines 41 to 49)
+ Data (lines 61 to 85)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ quantum defects in iodine atoms. The response
+ variable is the number of quantum defects, and the
+ predictor variable is the excited energy state.
+ The argument to the ARCTAN function is in radians.
+
+Reference: Roszman, L., NIST (19??).
+ Quantum Defects for Sulfur I Atom.
+
+
+
+
+
+
+Data: 1 Response (y = quantum defect)
+ 1 Predictor (x = excited state energy)
+ 25 Observations
+ Average Level of Difficulty
+ Observed Data
+
+Model: Miscellaneous Class
+ 4 Parameters (b1 to b4)
+
+ pi = 3.141592653589793238462643383279E0
+ y = b1 - b2*x - arctan[b3/(x-b4)]/pi + e
+
+
+ Starting Values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 0.1 0.2 2.0196866396E-01 1.9172666023E-02
+ b2 = -0.00001 -0.000005 -6.1953516256E-06 3.2058931691E-06
+ b3 = 1000 1200 1.2044556708E+03 7.4050983057E+01
+ b4 = -100 -150 -1.8134269537E+02 4.9573513849E+01
+
+Residual Sum of Squares: 4.9484847331E-04
+Residual Standard Deviation: 4.8542984060E-03
+Degrees of Freedom: 21
+Number of Observations: 25
+
+
+
+
+
+
+
+
+
+
+Data: y x
+ 0.252429 -4868.68
+ 0.252141 -4868.09
+ 0.251809 -4867.41
+ 0.297989 -3375.19
+ 0.296257 -3373.14
+ 0.295319 -3372.03
+ 0.339603 -2473.74
+ 0.337731 -2472.35
+ 0.333820 -2469.45
+ 0.389510 -1894.65
+ 0.386998 -1893.40
+ 0.438864 -1497.24
+ 0.434887 -1495.85
+ 0.427893 -1493.41
+ 0.471568 -1208.68
+ 0.461699 -1206.18
+ 0.461144 -1206.04
+ 0.513532 -997.92
+ 0.506641 -996.61
+ 0.505062 -996.31
+ 0.535648 -834.94
+ 0.533726 -834.66
+ 0.568064 -710.03
+ 0.612886 -530.16
+ 0.624169 -464.17
diff --git a/data/nist/Thurber.dat b/data/nist/Thurber.dat
new file mode 100644
index 0000000..6d72fd9
--- /dev/null
+++ b/data/nist/Thurber.dat
@@ -0,0 +1,97 @@
+NIST/ITL StRD
+Dataset Name: Thurber (Thurber.dat)
+
+File Format: ASCII
+ Starting Values (lines 41 to 47)
+ Certified Values (lines 41 to 52)
+ Data (lines 61 to 97)
+
+Procedure: Nonlinear Least Squares Regression
+
+Description: These data are the result of a NIST study involving
+ semiconductor electron mobility. The response
+ variable is a measure of electron mobility, and the
+ predictor variable is the natural log of the density.
+
+
+Reference: Thurber, R., NIST (197?).
+ Semiconductor electron mobility modeling.
+
+
+
+
+
+
+Data: 1 Response Variable (y = electron mobility)
+ 1 Predictor Variable (x = log[density])
+ 37 Observations
+ Higher Level of Difficulty
+ Observed Data
+
+Model: Rational Class (cubic/cubic)
+ 7 Parameters (b1 to b7)
+
+ y = (b1 + b2*x + b3*x**2 + b4*x**3) /
+ (1 + b5*x + b6*x**2 + b7*x**3) + e
+
+
+ Starting Values Certified Values
+
+ Start 1 Start 2 Parameter Standard Deviation
+ b1 = 1000 1300 1.2881396800E+03 4.6647963344E+00
+ b2 = 1000 1500 1.4910792535E+03 3.9571156086E+01
+ b3 = 400 500 5.8323836877E+02 2.8698696102E+01
+ b4 = 40 75 7.5416644291E+01 5.5675370270E+00
+ b5 = 0.7 1 9.6629502864E-01 3.1333340687E-02
+ b6 = 0.3 0.4 3.9797285797E-01 1.4984928198E-02
+ b7 = 0.03 0.05 4.9727297349E-02 6.5842344623E-03
+
+Residual Sum of Squares: 5.6427082397E+03
+Residual Standard Deviation: 1.3714600784E+01
+Degrees of Freedom: 30
+Number of Observations: 37
+
+
+
+
+
+
+
+Data: y x
+ 80.574E0 -3.067E0
+ 84.248E0 -2.981E0
+ 87.264E0 -2.921E0
+ 87.195E0 -2.912E0
+ 89.076E0 -2.840E0
+ 89.608E0 -2.797E0
+ 89.868E0 -2.702E0
+ 90.101E0 -2.699E0
+ 92.405E0 -2.633E0
+ 95.854E0 -2.481E0
+ 100.696E0 -2.363E0
+ 101.060E0 -2.322E0
+ 401.672E0 -1.501E0
+ 390.724E0 -1.460E0
+ 567.534E0 -1.274E0
+ 635.316E0 -1.212E0
+ 733.054E0 -1.100E0
+ 759.087E0 -1.046E0
+ 894.206E0 -0.915E0
+ 990.785E0 -0.714E0
+ 1090.109E0 -0.566E0
+ 1080.914E0 -0.545E0
+ 1122.643E0 -0.400E0
+ 1178.351E0 -0.309E0
+ 1260.531E0 -0.109E0
+ 1273.514E0 -0.103E0
+ 1288.339E0 0.010E0
+ 1327.543E0 0.119E0
+ 1353.863E0 0.377E0
+ 1414.509E0 0.790E0
+ 1425.208E0 0.963E0
+ 1421.384E0 1.006E0
+ 1442.962E0 1.115E0
+ 1464.350E0 1.572E0
+ 1468.705E0 1.841E0
+ 1447.894E0 2.047E0
+ 1457.628E0 2.200E0
