File: Lanczos1EM.txt

URL Reference: http://www.itl.nist.gov/div898/strd/nls/data/lanczos1.shtml

Dataset Name:  Lanczos1          (Lanczos1.dat)

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:   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

Mathematica Lists:
xLst = {0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.00, 1.05, 1.10, 1.15};

yLst = {2.513400000000, 2.044333373291, 1.668404436564, 1.366418021208, 1.123232487372, 0.9268897180037, 0.7679338563728, 0.6388775523106, 0.5337835317402, 0.4479363617347, 0.3775847884350, 0.3197393199326, 0.2720130773746, 0.2324965529032, 0.1996589546065, 0.1722704126914, 0.1493405660168, 0.1300700206922, 0.1138119324644, 0.1000415587559, 0.08833209084540, 0.07833544019350, 0.06976693743449, 0.06239312536719};

Maple Lists:
xLst := [0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.00, 1.05, 1.10, 1.15]:

yLst := [2.513400000000, 2.044333373291, 1.668404436564, 1.366418021208, 1.123232487372, 0.9268897180037, 0.7679338563728, 0.6388775523106, 0.5337835317402, 0.4479363617347, 0.3775847884350, 0.3197393199326, 0.2720130773746, 0.2324965529032, 0.1996589546065, 0.1722704126914, 0.1493405660168, 0.1300700206922, 0.1138119324644, 0.1000415587559, 0.08833209084540, 0.07833544019350, 0.06976693743449, 0.06239312536719]:

MATLAB Row Vectors:
xLst = [0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.00, 1.05, 1.10, 1.15];

yLst = [2.513400000000, 2.044333373291, 1.668404436564, 1.366418021208, 1.123232487372, 0.9268897180037, 0.7679338563728, 0.6388775523106, 0.5337835317402, 0.4479363617347, 0.3775847884350, 0.3197393199326, 0.2720130773746, 0.2324965529032, 0.1996589546065, 0.1722704126914, 0.1493405660168, 0.1300700206922, 0.1138119324644, 0.1000415587559, 0.08833209084540, 0.07833544019350, 0.06976693743449, 0.06239312536719];