Optimal sampling size in multivariate forest inventories: a programming procedure
1980 ◽
Vol 10
(4)
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pp. 579-585
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Use of mathematical programming has not become very common in determining optimal sample size in multivariate forest inventories. This paper illustrates the development of a model which may be solved using linear programming to yield a sampling distribution which is close to optimal. The reduction in sample size using the programming procedure over two approximate allocation methods is shown for two examples. It is concluded that the programming solution will show significant improvements over approximate procedures despite higher fixed costs in large multivariate inventories when the variables are not highly correlated and are considered of similar importance.
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2019 ◽
Vol 12
(08)
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pp. 1950086
2019 ◽
Vol 24
(10)
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pp. 761-769
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