Optimizing Forest Sampling by Using Lagrange Multipliers

• 作者: Kyriaki Kitikidou
• 来源期刊: 美国运筹学期刊(英文)
• 学科: 医学
• 关键词: FOREST Inventories LAGRANGE MULTIPLIERS OPTIMIZATION Sampling
• 年，卷（期）: 2012,（1）
• 页码范围: 94-99
• 页数: 6页
• 分类号: R73

摘要

In two-phase sampling, or double sampling, from a population with size N we take one, relatively large, sample size n. From this relatively large sample we take a small sub-sample size m, which usually costs more per sample unit than the first one. In double sampling with regression estimators, the sample of the first phase n is used for the estimation of the average of an auxiliary variable X, which should be strongly related to the main variable Y (which is estimated from the sub-sample m). Sampling optimization can be achieved by minimizing cost C with fixed var Y, or by finding a minimum var Y for fixed C. In this paper we optimize sampling with use of Lagrange multipliers, either by minimizing variance of Y and having predetermined cost, or by minimizing cost and having predetermined variance of Y.