[net.ai] Best fitting curve - 3 points

mwg@mouton.UUCP (06/25/84)

++
Since three points determine a parabola, just plug them into
y = Ax^2 + Bx + C and solve the system.  If you are in more than two
dimensions, you can probably do a transformation somehow into the
plane determined by the three points and solve; then translate back.
		-Mark

piety@hplabs.UUCP (Bob Piety) (06/26/84)

3 points can lie on a parabola, circle, cubic, or other shape.  There is not
enough information in just 3 points unless you know the nature of the curve.

Bob

gwyn@brl-vgr.ARPA (06/28/84)

Usually the correct approach is to take the parameterized curve that
is expected by theory to pass through the data and do a weighted (by
inverse error squared) least squares fit (i.e. determine the values
of the parameters that minimizes the weighted sum of the squares of
the deviations of the known data points from the curve).  One method
that works well is the Marquardt gradient-expansion technique described
in Bevington's "Data Reduction and Error Analysis for the Physical
Sciences".  Of course this assumes that you HAVE a theory...