We present a model construction method based on a local fitting of polynomial functions to noisy data and building the entire model as a union of regions explained by such polynomial functions. Local fitting is shown to reduce to solving a polynomial eigenvalue problem where the matrix coefficients are data covariance and approximated noise covariance matrices that capture distortion effects by...

Abstract. Taylor sections Sn(f) of an entire function f often provide easy computable polynomial approximants of f . However, while the rate of convergence of (Sn(f))n is nearly optimal on circles around the origin, this is no longer true for other plane sets as for example real compact intervals. The aim of this paper is to construct for certain families of (entire) functions sequences of poly...