On Discrete Least Squares Polynomial Fit, Linear Spaces and Data Classification
François Dubeau and Youness Mir
DOI : 10.3844/jmssp.2007.222.227
Journal of Mathematics and Statistics
Volume 3, 2007
The best discrete least squares polynomial fit to a data set is revisited. We point out some properties related to the best polynomial and precise the dimension of vector spaces encountered to solve the problem. Finally, we suggest a basic classification of data sets based on their increasing or decreasing trend, and on their convexity or concavity form.
© 2007 François Dubeau and Youness Mir. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.