svd_lls

svd_lls, a Python code which uses the Singular Value Decomposition (SVD) to construct and plot the best affine and linear relationships in the sense of least square, between two vectors of data.

The linear relationship will have the form

  ( y - mean(y) ) = slope * ( x - mean(x) )

The affine relationship will have the form

  y = slope * x + intercept

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Languages:

svd_lls is available in a MATLAB version and a Python version.

Related Data and Programs:

svd_snowfall, a Python code which reads a file containing historical snowfall data and analyzes the data with the singular value decomposition (SVD).

svd_test, a Python code which demonstrates the singular value decomposition (SVD) for a simple example.

Reference:

1. Lloyd Trefethen, David Bau,
   Numerical Linear Algebra,
   SIAM, 1997,
   ISBN: 0-89871-361-7,
   LC: QA184.T74.

Source Code:

• svd_lls.py calls all the tests.
• svd_lls.sh runs all the tests.
• svd_lls.txt the output file.

• sex_age_height_weight.txt records sex, age, height and weight for 237 students.
• hw_plot01.png plots height and weight.
• hw_plot02.png plots a linear relationship between centered height and weight.
• hw_plot03.png plots an affine relationship between height and weight.