• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.57-69
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• 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.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.27-34
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• 2004

The Horvitz-Thompson(H-T) estimator is less efficient than PPS estimators in some cases. We use the two-stage variable transformation in order to remove the drawbacks and increase the efficiency of H-T estimator. We transform the auxiliary variable to use the Midzuno-Sen sampling scheme at the first stage. And the next stage, we also transform the study variable to reduce the variance of H-T estimator using the inclusion probability obtained from the first transformation. We compare the efficiency between a suggested modified H-T estimator and PPS estimators.

• The Korean Journal of Applied Statistics
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• v.37 no.5
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• pp.663-673
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• 2024

The multi-armed bandits (MAB) problem, involves selecting actions to maximize rewards within dynamic environments. This study explores the application of Thompson sampling, a robust MAB algorithm, within the context of big data analytics and statistical learning theory. By leveraging large-scale banner click data from recommendation systems, we evaluate Thompson sampling's performance across various simulated scenarios, employing advanced approximation techniques. Our findings demonstrate that Thompson sampling, particularly with Langevin Monte Carlo approximation, maintains robust performance and scalability in big data environments. This underscores its practical significance and adaptability, aligning with contemporary challenges in statistical learning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1960-1963
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• 2021

In this paper, we propose a multiplay Thompson sampling algorithm in multipath communication system. Multipath communication system has advantages on communication capacity, robustness, survivability, and so on. It is important to select appropriate network path according to the status of individual path. However, it is hard to obtain the information of path quality simultaneously. To solve this issue, we propose Thompson sampling which is popular in machine learning area. We find some issues when the algorithm is applied directly in the proposal system and suggested some modifications. Through simulation, we verified the proposed algorithm can utilize the entire network paths. In summary, our proposed algorithm can be applied as a path allocation in multipath-based communications system.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.605-618
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• 2007

Adaptive sampling design is the selection procedure which depends on observed values of the variable of interest. It is the method which could be applied to the rare and unapproachable population. Adaptive cluster sampling strategies are more efficient than simple random sampling on equivalent sample size. Adaptive sampling with new estimators through the Rao-blackwell method have lower variance than Horvitz-Thompson (HT) and Hansen-Hurwitz (HH). Also, to determine suitable sample size, it was used expected sample and the method finding appropriate sample size by changing initial sample size were studied.

• Journal of the Korean Statistical Society
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• v.34 no.1
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• pp.73-83
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• 2005

Thompson's (1990) adaptive cluster sampling is a promising sampling technique to ensure effective representation of rare or localized population units in the sample. We consider the problem of simultaneous estimation of the numbers of earners through a number of rural unorganized industries of which some are concentrated in specific geographic locations and demonstrate how the performance of a conventional Rao-Hartley-Cochran (RHC, 1962) estimator can be improved upon by using auxiliary information in the form of generalized regression (greg) estimators and then how further improvements are also possible to achieve by adopting adaptive cluster sampling.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.889-900
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• 2008

Child labour is a disturbing issue for any society. It is attempted here in this article to develop an estimator to assess the numerical strength of this menace in Lahore division. A Horvitz and Thompson (1952) type of estimator is developed where weights are calculated on the basis of poverty and illiteracy to increase the sampling efficiency. Different characteristic features of this estimator, like its unbiasedness, variance, probability distribution, confidence intervals are also developed for its study from different angles.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.245-250
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• 2005

보통 생태학 분야 등에 적용될 수 있는 적응집락추출계획(adaptive cluster sampling plan)을 수정하여, 표본의 크기 면에서 더 효율적인 Jumped 및 일반화 적응집락추출계획을 제안하였다. 이러한 계획 하에서 Hansen-Hurwitz(HH)와 Horvitz-Thompson (HT) 추정량으로 모수를 추정하였다. 제안한 새로운 계획들을 시뮬레이션을 통하여 기존의 계획과 비교하였다.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1199-1210
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• 2017

A new in-line method for sampling neutrons emitted in (${\alpha}$,n) reactions based on alpha particle source information has been developed for continuous-energy Monte Carlo simulations. The new method uses a continuous-slowing-down model coupled with (${\alpha}$,n) cross section data to precompute the expected neutron yield over the alpha particle lifetime. This eliminates the complexity and computational cost associated with explicit charged particle transport. When combined with an integrated alpha particle decay source sampling capability, the proposed method provides an efficient and accurate method for sampling (${\alpha}$,n) neutrons based solely on nuclide inventories in the problem, with no additional user input required. Results from several example calculations show that the proposed method reproduces the (${\alpha}$,n) neutron yields and energy spectra from reference experiments and calculations.

• Journal of the Korean earth science society
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• v.27 no.1
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• pp.73-82
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• 2006

Dust samples were collected from 10 middle and high schools in the Gochang-Gun, Korea. Heavy metal concentrations were determined for the dry-deposited dusts from indoor and outdoor of classroom and playground of each sampling site. Concentrations of Cd, Cu, Pb and Zn in indoor's dusts were highly concentrated. Also concentrations of Cu, Ni, Pb and Zn in outdoor's dusts were highly concentrated. Concentrations of Cd, Cu and Zn in the dusts were much higher than the world average contents in soil and environmental orientation value. These levels are similar to those of the dust samples at middle schools and high schools located in Jeonju-city, Korea. Compared with concentrations of heavy metals in soils and dusts in Korea, the environment of indoor and outdoor of classroom is highly concentrated except for Cu, Zn. The concentrations of playground is less than that of residential dust and main road dust and playground in Jeonju-city. Playground dusts in 1 school exhibited the enhanced heavy metal pollution with a pollution index (Kloke, 1979) greater than 1.0, but indoor and outdoor dusts in 7 schools exhibited the enhanced heavy metal pollution with a pollution index (by Kloke) yester than 1.0.