Convergence of polynomial least squares end-point and mid-point estimators

1 March 1983

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in Proceedings of the IEEE

Vol. 71 (3) , 441-442
https://doi.org/10.1109/PROC.1983.12604

Abstract

In a recent corcespondence, Leskiw and Miller [1] obtained the variance of a least squares polynomial estimator, as function of the polynomial order, for a large number of equally spaced data points, when the estimate is for the end-point. A simpler proof is given, and the result is extended to the mid-point. A mid-point estimator may be of special interest since it exhibits the lowest variance.

Keywords

CONVERGENCE
POLYNOMIALS
LEAST SQUARES APPROXIMATION
REACTIVE POWER
COVARIANCE MATRIX
ADDITIVE NOISE
NETWORK ADDRESS TRANSLATION
ANALYSIS OF VARIANCE
PHYSICS COMPUTING
INTEGRAL EQUATIONS

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