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Construction of resolvable spatial row-column designs
E R Williams1, J A John, D Whitaker
1CSIRO Forestry and Forest Products, P.O. Box E4008, Kingston, ACT 2604, Australia. emlyn.williams@csiro.au
Resolvable row-column designs enhance field trial precision. This study extends spatial block design principles using the two-dimensional linear variance (LV) model for more efficient experimental layouts.
Area of Science:
- Agricultural Science
- Experimental Design
- Statistical Modeling
Background:
- Resolvable row-column designs are crucial for controlling variation in field trials.
- Spatial models and incomplete blocking can further enhance experimental precision.
- Previous work by Martin et al. established principles for robust spatial block designs using the linear variance (LV) model.
Purpose of the Study:
- To define the two-dimensional linear variance (LV) model.
- To extend existing principles for constructing resolvable spatial row-column designs.
- To investigate efficient computer-aided construction of these designs.
Main Methods:
- Definition of the two-dimensional linear variance (LV) model.
- Adaptation of Martin et al.'s principles for spatial row-column designs.
- Exploration of computer algorithms for design construction.
Main Results:
- The study defines the two-dimensional LV model and its application to row-column designs.
- Extensions of general principles for constructing efficient resolvable spatial designs are presented.
- Comparisons are made with designs based on autoregressive variance structures.
Conclusions:
- The two-dimensional LV model provides a framework for advanced spatial experimental designs.
- The extended principles facilitate the construction of efficient and precise resolvable spatial row-column designs.
- Computer construction methods are vital for generating optimal designs in complex field trials.
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