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Optimum design for correlated processes via eigenfunction expansions

2004/01/01 by V. V. Fedorov, Fedorov, Valery V., Werner G. Müller +1 · 1 citation
Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Optimal Experimental Design Methods #Probabilistic and Robust Engineering Design

paper · doi:10.57938/988141ec-5134-4759-9197-53836eaba12f

openalex publication_date 2004/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

In this paper we consider optimum design of experiments for correlated observations. We approximate the error component of the process by an eigenvector expansion of the corresponding covariance function. Furthermore we study the limit behavior of an additional white noise as a regularization tool. The approach is illustrated by some typical examples. (authors' abstract)

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