Source code for naginterfaces.library.examples.correg.glm_normal_ex

#!/usr/bin/env python3
"``naginterface.library.correg.glm_normal`` Python Example."

# NAG Copyright 2017-2019.

# pylint: disable=invalid-name,too-many-locals

from naginterfaces.library import correg

def main():
    """
    Example for :func:`naginterfaces.library.correg.glm_normal`.

    Fits a generalized linear model with Normal errors.

    >>> main()
    naginterfaces.library.correg.glm_normal Python Example Results.
    Fits a generalized linear model with Normal errors.
    Fitted model summary:
    RSS is 3.872e-01
    Degrees of freedom 3
    Term         Estimate   Standard Error
    Variable:  0 -2.387e-02   2.779e-03
    Variable:  1 6.381e-02   2.638e-03
    """

    print('naginterfaces.library.correg.glm_normal Python Example Results.')
    print('Fits a generalized linear model with Normal errors.')

    # The observations:
    x = [
        [1.],
        [2.],
        [3.],
        [4.],
        [5.],
    ]
    # Other parameters for the fit:
    link = 'Reciprocal'
    isx = [1]
    y = [
        25., 10., 6., 4., 3.,
    ]
    tol = 5.e-5
    eps = 1.e-6

    fit = correg.glm_normal(
        x, isx, y, link=link, tol=tol, eps=eps,
    )

    print('Fitted model summary:')
    print('RSS is {:.3e}'.format(fit.rss))
    print('Degrees of freedom {:d}'.format(fit.idf))

    print('Term' + ' '*9 + 'Estimate' + ' '*3 + 'Standard Error')
    for i, b_i in enumerate(fit.b):
        print('Variable:' + ' '*2 + '{:d} {:.3e}   {:.3e}'.format(
            i, b_i, fit.se[i]
        ))

if __name__ == '__main__':
    import doctest
    import sys
    sys.exit(
        doctest.testmod(
            None, verbose=True, report=False,
            optionflags=doctest.REPORT_NDIFF,
        ).failed
    )