Results 1 to 10 of about 4,194,931 (278)
On use of adaptive cluster sampling for variance estimation [PDF]
Journal of Applied StatisticsAdaptive cluster sampling is particularly helpful whenever the target population is unique, dispersed unevenly, concealed or difficult to find. In the current investigation, under an adaptive cluster sampling approach, we propose a ratio-product-logarithmic type estimator employing a single auxiliary variable for the estimation of finite population ...
Javid Shabbir, Shameem Alam
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Modified Adaptive Cluster Sampling Designs [PDF]
Communications for Statistical Applications and Methods, 2007 Adaptive cluster sampling design is known as a sampling method for rare clustered population. Three modified adaptive cluster sampling designs are proposed. The adjusted Hansen-Hurwitz estimator and the Horvitz-Thompson estimator are considered. Efficiency issue of the proposed sampling designs is discussed in a Monte-Carlo simulation study.
Chang-Kyoon Son
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Partial systematic adaptive cluster sampling
Environmetrics, 2012 A main benefit from taking a systematic sample is the ease of implementation when field sampling. However, it is not uncommon for a researcher to sample only one primary sampling unit (PSU) but to assume that the secondary sampling units (SSUs) were selected by simple random sampling to obtain a variance estimate.
David Smith
exaly +3 more sources
PLoS ONE, 2021 Sampling rare and clustered populations is challenging because of the effort required to find rare units. Heuristically, a practitioner would prefer to discontinue sampling in areas where rare units of interest are apparently extremely sparse or absent ...
Mohammad Salehi, David R Smith
doaj +1 more source
Arithmetic, 2023 This research aims to determine the effect of the CPS learning model on mathematical adaptive reasoning ability in terms of students' entrepreneurial character.
Komarudin Komarudin +4 more
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Journal of Forest Science, 2012 Based on two species of Coastal Mangrove in Hainan of China, Sonneratia Apetala Buch-Ham and Sonneratia caseoli, we estimated the density of the two species to evaluate the efficiency of adaptive cluster sampling (ACS), simple random sampling (SRS) and ...
Y. Lei, J. Shi, T. Zhao
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Fast and interpretable consensus clustering via minipatch learning.
PLoS Computational Biology, 2022 Consensus clustering has been widely used in bioinformatics and other applications to improve the accuracy, stability and reliability of clustering results.
Luqin Gan, Genevera I Allen
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DisSAGD: A Distributed Parameter Update Scheme Based on Variance Reduction
Sensors, 2021 Machine learning models often converge slowly and are unstable due to the significant variance of random data when using a sample estimate gradient in SGD.
Haijie Pan, Lirong Zheng
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On two-stage adaptive cluster sampling to assess pest density
浙江大学学报. 农业与生命科学版, 2000 The adaptive cluster sampling introduced by Thompson is a powerful method for a survey of a population which is highly clumped with clumps widely separated.
ZHANG Nan-song +2 more
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Inventory of sparse forest populations using adaptive cluster sampling
Silva Fennica, 2006 In many studies, adaptive cluster sampling (ACS) proved to be a powerful tool for assessing rare clustered populations that are difficult to estimate by means of conventional sampling methods.
Talvitie, Mervi +2 more
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