Abstract.Fitting circles and ellipses to given points in the plane is a problem that arises in many application areas, e.g., computer graphics, coordinate meteorology, petroleum engineering, statistics. In the past, algorithms have been given which fit circles and ellipses in some least-squares sense without minimizing the geometric distance to the given points.In this paper we present several algorithms which compute the ellipse for which the sum of the squares of the distances to the given points is minimal. These algorithms are compared with classical simple and iterative methods.Circles and ellipses may be represented algebraically, i.e., by an equation of the form F(x) = 0. Ifa point is on the curve, then its coordinates x are a zero of the function F. Alternatively, curves may be represented in parametric form, which is well suited for minimizing the sum of the squares of the distances.

Summary.We present the theory of the linear least squares problem with a quadratic constraint. New theorems characterizing properties of the solutions are given. A numerical application is discussed.

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