Influence of missing data on compact designs for spacing experiments
- 1 November 2002
- journal article
- research article
- Published by Taylor & Francis in Journal of Applied Statistics
- Vol. 29 (8) , 1229-1240
- https://doi.org/10.1080/0266476022000011292
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.Keywords
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