Results 261 to 270 of about 60,047 (288)

Variance estimation in adaptive cluster sampling

Communications in Statistics - Theory and Methods, 2019
In this paper, a class of variance estimator is proposed of a finite population variance under an adaptive cluster sampling design in the presence of information on an auxiliary variable.
Uzma Yasmeen, Mary Thompson
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Stratified adaptive cluster sampling

Biometrika, 1991
SUMMARY Stratified adaptive cluster sampling refers to designs in which, following an initial stratified sample, additional units are added to the sample from the neighbourhood of any selected unit with an observed value that satisfies a condition of interest.
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Stratified Inverse Adaptive Cluster Sampling

2021
In forestry and environmental sciences, some species of plants and animals are rare and clustered, i.e., abundance of zeros. The traditional sampling methods provide poor estimates of the population mean/total. In such situations, adaptive sampling is useful.
Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra   +3 more
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Adaptive sampling without replacement of clusters

Statistical Methodology, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dryver, Arthur L., Thompson, Steven K.
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Adaptive cluster path sampling

Communications in Statistics - Simulation and Computation, 2022
Mena Lao, Arthur Dryver
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Model-based adaptive cluster sampling [PDF]

, 2004
The general theory for making maximum likelihood (model-based) inference from sample survey data is presented in Breckling et al. (1994).  We present an overview of this theory and use this to create a model-based approach to analysing sparse, clustered data. The ideas contained within Breckling et al.
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Estimation of rare and clustered population variance in adaptive cluster sampling

Communications in Statistics - Theory and Methods, 2018
Many researchers used auxiliary information together with survey variable to improve the efficiency of population parameters like mean, variance, total and proportion.
Muhammad Nouman Qureshi, Sadia Khalil, Chang-Tai Chao, Muhammad Hanif   +3 more
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Adaptive Cluster Sampling in the Context of Restoration

Restoration Ecology, 2012
AbstractAbundance is an important population state variable for monitoring restoration progress. Efficient sampling often proves difficult, however, when populations are sparse and patchily distributed, such as early after restoration planting. Adaptive cluster sampling (ACS) can help by concentrating search effort in high density areas, improving the ...
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Designing an efficient adaptive cluster sample

Environmental and Ecological Statistics, 2003
The choice of neighborhood definition and critical value in adaptive cluster sampling is critical for designing an efficient survey. In designing an efficient adaptive cluster sample one should aim for a small difference between the initial and final sample size, and a small difference between the within-network and population variances.
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A Bootstrap Method for Adaptive Cluster Sampling

1999
In adaptive designs defined by selecting an initial simple random sample with or without replacement, the sample mean estimator is unbiased only if the initial sample is used, whereas, it is biased when a sample obtained at the end of the adaptive procedure is considered.
Tonio Di Battista, Domenico Di Spalatro
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