Generalizing from a straight line (i.e., first degree polynomial) to a th degree polynomial
| (1) |
the residual is given by
| (2) |
The partial derivatives (again dropping superscripts) are
| (3) | |||
| (4) | |||
| (5) |
These lead to the equations
| (6) | |||
| (7) | |||
| (8) |
or, in matrix form
| (9) |
This is a Vandermonde matrix. We can also obtain the matrix for a least squares fit by writing
| (10) |
Premultiplying both sides by the transpose of the first matrix then gives
| (11) |
so
| (12) |
As before, given points
and fitting with polynomial coefficients
, ...,
gives
| (13) |
In matrix notation, the equation for a polynomial fit is given by
| (14) |
This can be solved by premultiplying by the transpose ,
| (15) |
This matrix equation can be solved numerically, or can be inverted directly if it is well formed, to yield the solution vector
| (16) |
Setting in the above equations reproduces the linear solution.