Abstract
The design of experiments when the data are correlated is an area of increasing research interest, particularly since methods for the analysis of experiments which incorporate a correlation structure for errors or over the plots are becoming more generally applied. In this paper the design of experiments of a two-dimensional layout (rows and columns) with a spatial process is investigated. Algorithms based on simulated annealing and Tabu search are developed for constructing optimal designs. The robustness of designs with respect to correlation structure is examined. A number of examples are considered including a practical example of an early generation variety trial example is given.
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© 1998 Springer-Verlag Berlin Heidelberg
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Eccleston, J., Chan, B. (1998). Design Algorithms for Correlated Data. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_4
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DOI: https://doi.org/10.1007/978-3-662-01131-7_4
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1131-5
Online ISBN: 978-3-662-01131-7
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