Least Squares Function Approximation

A method for approximating the best line corresponding to experimental data X and Y in the form of y=a+bx and a seperate method for the special case of a=0 thus y=bx.

Example

Command Window

leastSquares([0 1 2 3 4 5 6 7 8 9],[4.6 7.1 9.5 11.5 13.7 15.9 18.6 20.9 23.5 25.4])

n =

    10


sumX =

    45


sumX2 =

   285


sumY =

     1.507000000000000e+02


sumXY =

     8.694000000000000e+02


a =

   4.638181818181827


b =

   2.318181818181817


sumD2 =

   0.348727272727272


da =

   0.122713803974738


db =

   0.022986401537591

Figure

Issues

There are no known issues. The main method has been tested and is working whilst the y=bx method has not, though it should theoretically work.