New submission from Raymond Hettinger <raymond.hettin...@gmail.com>:
Signature:
def linear_regression(x, y, /, *, proportional=False):
Additional docstring with example:
If *proportional* is true, the independent variable *x* and the
dependent variable *y* are assumed to be directly proportional.
The data is fit to a line passing through the origin.
Since the *intercept* will always be 0.0, the underlying linear
function simplifies to:
y = slope * x + noise
>>> y = [3 * x[i] + noise[i] for i in range(5)]
>>> linear_regression(x, y, proportional=True) #doctest: +ELLIPSIS
LinearRegression(slope=3.0244754248461283, intercept=0.0)
See Wikipedia entry for regression without an intercept term:
https://en.wikipedia.org/wiki/Simple_linear_regression#Simple_linear_regression_without_the_intercept_term_(single_regressor)
Compare with the *const* parameter in MS Excel's linest() function:
https://support.microsoft.com/en-us/office/linest-function-84d7d0d9-6e50-4101-977a-fa7abf772b6d
Compare with the *IncludeConstantBasis* option in Mathematica:
https://reference.wolfram.com/language/ref/IncludeConstantBasis.html
----------
components: Library (Lib)
messages: 406026
nosy: rhettinger, steven.daprano
priority: normal
severity: normal
status: open
title: Add direct proportion option to statistics.linear_regression()
versions: Python 3.11
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Python tracker <rep...@bugs.python.org>
<https://bugs.python.org/issue45766>
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