Abstract
By using the alternating projection theorem of J. von Neumann, we obtain explicit formulae for the best linear interpolator and interpolation error of missing values of a stationary process. These are expressed in terms of multistep predictors and autoregressive parameters of the process. The key idea is to approximate the future by a finite-dimensional space.
Publisher
Cambridge University Press (CUP)
Subject
Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability
Cited by
2 articles.
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1. On linear prediction for stationary random fields with nonsymmetrical half-plane past;Communications in Statistics - Theory and Methods;2020-10-22
2. Some extremal problems in ^{}();Proceedings of the American Mathematical Society;1998