This file is indexed.

/usr/share/gretl/data/nist/Wampler2.dat is in gretl-data 2016d-1.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
NIST/ITL StRD
Dataset Name:  Wampler2 (Wampler2.dat)

File Format:   ASCII
               Certified Values  (lines 31 to 50)
               Data              (lines 61 to 81)

Procedure:     Linear Least Squares Regression

Reference:     Wampler, R. H. (1970). 
               A Report of the Accuracy of Some Widely-Used Least 
               Squares Computer Programs. 
               Journal of the American Statistical Association, 65, pp. 549-565.
           
Data:          1 Response Variable (y)
               1 Predictor Variable (x)
               21 Observations
               Higher Level of Difficulty
               Generated Data

Model:         Polynomial Class
               6 Parameters (B0,B1,...,B5)

               y = B0 + B1*x + B2*(x**2) + B3*(x**3)+ B4*(x**4) + B5*(x**5)

               Certified Regression Statistics

                                           Standard Deviation
     Parameter         Estimate               of Estimate

        B0        1.00000000000000         0.000000000000000
        B1        0.100000000000000        0.000000000000000
        B2        0.100000000000000E-01    0.000000000000000
        B3        0.100000000000000E-02    0.000000000000000
        B4        0.100000000000000E-03    0.000000000000000
        B5        0.100000000000000E-04    0.000000000000000

     Residual
     Standard Deviation   0.000000000000000

     R-Squared            1.00000000000000


               Certified Analysis of Variance Table

Source of Degrees of     Sums of               Mean  
Variation  Freedom       Squares              Squares           F Statistic
              
Regression   5       6602.91858365167     1320.58371673033       Infinity
Residual    15       0.000000000000000    0.000000000000000









Data:          y       x
            1.00000    0
            1.11111    1
            1.24992    2
            1.42753    3
            1.65984    4
            1.96875    5
            2.38336    6
            2.94117    7
            3.68928    8
            4.68559    9
            6.00000   10
            7.71561   11
            9.92992   12
           12.75603   13
           16.32384   14
           20.78125   15
           26.29536   16
           33.05367   17
           41.26528   18
           51.16209   19
           63.00000   20