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Two-Stage Adaptive Cluster Sampling
Biometrics, 1997Summary: Adaptive cluster sampling is a powerful method for parameter estimation when a population is highly clumped with clumps widely separated. Unfortunately, its use has been somewhat limited until now because of the lack of a suitable theory for using a pilot survey to design an experiment with a given efficiency or expected cost.
Salehi M., Mohammad, Seber, George A. F.
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Double Sampling for Cluster- or Two-Stage Sampling
International Statistical Review / Revue Internationale de Statistique, 1972Survey sampling literature describes several methods of using certain auxiliary information to attain more efficient sampling and estimation procedures. If the required information is not available in advance for the entire population, it might be advantageous to collect certain items for a larger, preliminary sample and then use this to improve on the
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Stepwise two‐stage sample size adaptation
Statistics in Medicine, 2014Several adaptive design methods have been proposed to reestimate sample size using the observed treatment effect after an initial stage of a clinical trial while preserving the overall type I error at the time of the final analysis. One unfortunate property of the algorithms used in some methods is that they can be inverted to reveal the exact ...
Hong Wan +2 more
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A two‐stage sampling for robust feature matching
Journal of Field Robotics, 2018AbstractFor any visual feature‐based SLAM (simultaneous localization and mapping) solutions, to estimate the relative camera motion between two images, it is necessary to find “correct” correspondence between features extracted from those images. Given a set of feature correspondents, one can use a n‐point algorithm with robust estimation method, to ...
Chih-Chung Chou +2 more
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Two-Stage Sampling with Exchangeable Prior Distributions
Biometrika, 1977Consider a two-stage population of K primary units, consisting respectively of M1, ..., MK secondary units. Denote the characteristic values by yii. Assume a class of priors under which yii for fixed i are the first Mi elements of the ith row of a rectangular array such that (i) the row vectors are exchangeable, and (ii) elements within rows are ...
Bellhouse, D. R. +2 more
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Application of Two-Stage Sampling in Sampling Inspection
2021This paper considers conditioning on the quantities of the samples observed in incoming inspection, we give the sampling characteristic function and algorithm of the two-stage sampling scheme. Based on the comparison of operating characteristic curves we found that the sample size of the sampling scheme proposed in this paper is one-tenth of the ...
Jinzhuo Chen, Tao Hong
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Two-Stage Negative Adaptive Cluster Sampling
Communications in Mathematics and Statistics, 2018The authors deal with adaptive cluster sampling, a better alternative of the simple random sampling in cases when the population is rare and clustered. With this approach, auxiliary information is often used in order to overcome the problem with the increasing sample size.
Latpate, R. V., Kshirsagar, J. K.
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On Sample Size and Inference for Two‐Stage Adaptive Designs
Biometrics, 2001Summary. Proschan and Hunsberger (1995, Biometrics51, 1315–1324) proposed a two‐stage adaptive design that maintains the Type I error rate. For practical applications, a two‐stage adaptive design is also required to achieve a desired statistical power while limiting the maximum overall sample size.
Liu, Qing, Chi, George Y. H.
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Two-Stage Adaptive Cluster Sampling
2021Adaptive sampling is a method in which selection of units at any stage of sampling depends upon the information collected from the already selected units in the initial sample. It means, if one finds what he/she is looking for at a particular location then he/she would sample in the vicinity of that location with the hope of obtaining more information.
Raosaheb Latpate +3 more
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Estimating the Mean by Two-Stage Sampling with Replacement
Calcutta Statistical Association Bulletin, 1963Summary In two-stage sampling when sampling is done with replacement at each stage, a better estimate of the population mean can be obtained by considering the distinct units only at each stage. The mean of the distinct uniss is chosen as the desired estimate and an exact expression for the variance is obtained. A sufficient condition
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