A Jackknife Estimator of Variance for a Random Tessellated Stratified Sampling Design. Issue 5 (12th March 2019)

• Record Type: Journal Article
• Authors: Magnussen, Steen; Nord-Larsen, Thomas
• Is Part Of: Forest science. Volume 65:Issue 5(2019)
• Page Start: 543
• Page End: 547
• Publication Date: 2019-03-12
• Subjects: semisystematic sampling -- spatial balance -- National Forest Inventory -- model-assisted ratio of totals estimator -- LiDAR -- auxiliary variables; Forests and forestry -- Periodicals; Forest management -- Periodicals; Forest policy -- United States -- Periodicals; Forest management; Forest policy; Forests and forestry; United States; Electronic journals; Periodicals; 634.9
• DOI: 10.1093/forsci/fxy070
• Languages: English
• ISSNs: 0015-749X

Abstract

Abstract: Semisystematic sampling designs—in which a population area frame is tessellated into cells, and a randomly located sample is taken from each cell—affords random tessellated stratified (RTS) Horvitz–Thompson-type estimators. Forest inventory applications with RTS estimators are rare, possibly because of computational complexities with the estimation of variance. To reduce this challenge, we propose a jackknife estimator of variance for RTS designs. We demonstrate an application with a model-assisted ratio of totals estimator and data from the Danish National Forest Inventory. RTS estimators of standard error were, as a rule, smaller than comparable estimates obtained under the assumption of simple random sampling. The proposed jackknife estimator performed well.