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Influence of missing data on compact designs for spacing experiments

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  • Avner Bar-Hen

Abstract

Density optimization of a plantation is a classical task with important practical consequences. In this article, we present an adaptation of criss-cross design and an alternative analysis. If a tree is missing, the spacing of neighbouring trees is altered and considerable information is lost. We derive the estimate of the missing value that minimizes the residual sum of squares and obtain the analytical solution of the EM algorithm. The relationships between the two techniques are clarified. The method is applied to data from a plantation of Eucalyptus in the Congo.

Suggested Citation

  • Avner Bar-Hen, 2002. "Influence of missing data on compact designs for spacing experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(8), pages 1229-1240.
    • Handle: RePEc:taf:japsta:v:29:y:2002:i:8:p:1229-1240
    DOI: 10.1080/0266476022000011292
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    References listed on IDEAS

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    1. Michael Healy & Michael Westmacott, 1956. "Missing Values in Experiments Analysed on Automatic Computers," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 5(3), pages 203-206, November.
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