A jackknife variance estimator for unequal probability sampling

2005 ◽  
Vol 67 (1) ◽  
pp. 79-89 ◽  
Author(s):  
Yves G. Berger ◽  
Chris J. Skinner
Keyword(s):  
Variance Estimator ◽  
Probability Sampling ◽  
Unequal Probability Sampling ◽  
Unequal Probability

scholarly journals On a Scheme of Sampling of Two Units With Inclusion With Inclusion

2016 ◽  
Vol 35 (4) ◽  
Author(s):  
Sarat C. Senapati ◽  
L.N. Sahoo ◽  
G. Mishra
Keyword(s):  
Auxiliary Variable ◽  
Variance Estimator ◽  
Inclusion Probability ◽  
Sampling Without Replacement ◽  
Probability Sampling ◽  
Sampling Schemes ◽  
Unequal Probability Sampling ◽  
Unequal Probability ◽  
Replacement Scheme

This paper introduces an unequal probability sampling without replacement scheme with inclusion probability proportional to size. This new scheme possesses some desirable properties with regard to ?i and ?ij , and provides a non-negative variance estimator of the Horvitz and Thompson estimator, when the values of the auxiliary variable fulfill some restrictions. On comparing the suggested scheme with some of the existing sampling schemes in respect of efficiency and stability of the variance estimator empirically, it has been observed that the performance of the scheme is satisfactory.

Evaluation of sampling alternatives to quantify tree leaf area

2003 ◽  
Vol 33 (1) ◽  
pp. 82-95 ◽  
Author(s):  
H Temesgen
Keyword(s):  
Leaf Area ◽  
Poor Performance ◽  
Tree Crown ◽  
Two Stage ◽  
Zero Bias ◽  
Probability Sampling ◽  
First Order ◽  
Unequal Probability Sampling ◽  
Unequal Probability ◽  
Tree Leaf

High within- and among-tree crown variation have contributed to the difficulty of tree-crown sampling and single-tree leaf area (area available for photosynthesis) estimation. Using reconstructed trees, simulations were used to compare five sampling designs for bias, mean square error (MSE), and distribution of the estimates. All sampling designs showed nearly zero bias. For most sample trees, stratified random sampling resulted in the lowest MSE values, followed by ellipsoidal, two-stage systematic, simple random, and then by two-stage unequal probability sampling. The poor performance of two-stage unequal probability sampling can be ascribed to the unequal probability of inclusion of first-order branches and twigs.

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