• 제목/요약/키워드: Sequential sampling

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On the Bayes risk of a sequential design for estimating a mean difference

  • Sangbeak Ye;Kamel Rekab
    • Communications for Statistical Applications and Methods
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    • 제31권4호
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    • pp.427-440
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    • 2024
  • The problem addressed is that of sequentially estimating the difference between the means of two populations with respect to the squared error loss, where each population distribution is a member of the one-parameter exponential family. A Bayesian approach is adopted in which the population means are estimated by the posterior means at each stage of the sampling process and the prior distributions are not specified but have twice continuously differentiable density functions. The main result determines an asymptotic second-order lower bound, as t → ∞, for the Bayes risk of a sequential procedure that takes M observations from the first population and t - M from the second population, where M is determined according to a sequential design, and t denotes the total number of observations sampled from both populations.

Efficient Sequential Estimation in a Compound Poisson Process

  • Bai, Do-Sun;Kim, Myung-Soo;Jang, Joong-Soon
    • Journal of the Korean Statistical Society
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    • 제15권2호
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    • pp.87-96
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    • 1986
  • Sequential estimation of parameters in a compound Poisson process whose jump sizes are one-parameter exponential class random variables is discussed. Cramer-Rao type information inequality is used as an efficiency cirterion. Unbiased estimators for certain parametric functions whose variance attain the lower bound are all characterized with the corresponding sampling plans.

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A Bayes Sequential Selection of the Least Probale Event

  • Hwang, Hyung-Tae;Kim, Woo-Chul
    • Journal of the Korean Statistical Society
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    • 제11권1호
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    • pp.25-35
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    • 1982
  • A problem of selecting the least probable cell in a multinomial distribution is studied in a Bayesian framework. We consider two loss components the cost of sampling and the difference in cell probabilities between the selected and the least probable cells. A Bayes sequential selection rule is derived with respect to a Dirichlet prior, and it is compared with the best fixed sample size selection rule. The continuation sets with respect to the vague prior are tabulated for certain cases.

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단축-축차관리도의 설계 (Design of a Curtailed-SPRT Control Chart)

  • 장영순
    • 한국경영과학회지
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    • 제34권1호
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    • pp.29-37
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    • 2009
  • This paper proposes a curtailed-sequential probability ratio test (SPRT) control chart. For using the conventional SPRT control chart, the number of items inspected in a sampling point should have no restriction since items in a sampling point are inspected one by one until an SPRT Is terminated. The number of observations taken in a sampling point, however, has an upper bound since sampling and testing of an item is time-consuming or expensive. When the sample size reaches the upper bound without evidence of an in-control or out-of-control state of a process, the proposed chart makes a decision using the sample mean of all observations taken in a sampling point. The properties of the Proposed chart are obtained by a Markov chain approach and the performance of the chart is compared with fixed sample size (FSS) and variable sample size (VSS) control charts. A comparative study shows that the proposed chart performs better than VSS control charts as well as conventional FSS control charts.

A Study on Optimal sampling acceptance plans with respect to a linear loss function and a beta-binomial distribution

  • Kim, Woo-chul;Kim, Sung-ho
    • 품질경영학회지
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    • 제10권2호
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    • pp.25-33
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    • 1982
  • We discuss a model for acceptance/rejection decision regarding finite populations. The model is based on a beta-binomial prior distribution and additive costs -- relative sampling costs, relative sorting costs and costs of accepted defectives. A substantial part of the paper is devoted to constructing a Bayes sequential sampling acceptance plan (BSSAP) for attributes under the model. It is shown that the Bayes fixed size sampling acceptance plans (BFSAP) are better than the Hald's (1960) single sampling acceptance plans based on a uniform prior. Some tables and examples are provided for comprisons of the minimum Bayes risks of the BSSAP and those of the BFSAP based on a uniform prior and the model.

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시뮬레이션 기반 반도체 포토공정 스케줄링을 위한 샘플링 대안 비교 (A Simulation-based Optimization for Scheduling in a Fab: Comparative Study on Different Sampling Methods)

  • 윤현정;한광욱;강봉권;홍순도
    • 한국시뮬레이션학회논문지
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    • 제32권3호
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    • pp.67-74
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    • 2023
  • 반도체 제조라인(FAB)은 복잡하고 불확실한 운영환경에서 작동하는 대규모의 제조시스템 중 하나로 반도체 설비 운영을 담당하는 엔지니어들은 직관적이고 신속한 공정 스케줄링을 위해 가중치 기반 스케줄링을 널리 사용하고 있다. 가중치 기반 스케줄링에서 가중치 결정은 FAB 성능에 큰 영향을 미치므로 엔지니어들은 가중치 최적화를 위하여 시뮬레이션 기반 의사결정을 활용할 수 있다. 그러나 대규모 시뮬레이션은 많은 실험 비용을 요구하기 때문에 효과적인 의사결정을 위해서 신중한 실험설계가 요구된다. 본 연구에서는 적은 시뮬레이션 실행 내에서 효율적인 스케줄링을 도출하기 위해 세 가지 샘플링 대안(i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search (DSS))에 대한 비교연구를 수행하였다. 시뮬레이션 실험을 통해 세 가지 대안이 단일 규칙보다 우수한 성능을 보였고, 그중 GA와 DSS가 최적화를 위한 효과적인 대안이 될 수 있음을 확인하였다.

정량 정보를 포함한 순차 패턴 마이닝 알고리즘 (Sequential Pattern Mining Algorithms with Quantities)

  • 김철연;임종화;;심규석
    • 한국정보과학회논문지:데이타베이스
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    • 제33권5호
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    • pp.453-462
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    • 2006
  • 순차 패턴을 찾는 것은 데이타마이닝 응용분야에서 중요한 문제이다. 기존의 순차 패턴 마이닝 알고리즘들은 아이템으로만 이루어진 순차 패턴만을 취급하였으나 경제나 과학분야와 같은 많은 분야에서는 정량 정보가 아이템과 같이 기록되어 있으며, 기존의 알고리즘이 처리하지 못하는 이러한 정량 정보는 사용자에게 보다 유용한 정보를 전달하여 줄 수 있다. 본 논문에서는 정량 정보를 포함한 순차패턴 마이닝 문제를 제안하였다. 기존의 순차패턴 알고리즘에 대한 단순한 확장으로는 모든 정량에 대한 후보 패턴들을 모두 생성하기 때문에 확대된 탐색 공간을 효율적으로 탐색할 수 없음을 보이고, 이러한 단순한 확장 알고리즘의 성능을 대폭 향상시키기 위하여 정량 정보에 대해 해쉬 필터링과 정량 샘플링 기법을 제안하였다. 다양한 실험 결과들은 제안된 기법들이 단순히 확장된 알고리즘과 비교하여 수행시간을 매우 단축시켜 줄 뿐만 아니라, 데이타베이스 크기에 대한 확장성 또한 향상시켜줌을 보여 준다.

Sequential fusion to defend against sensing data falsification attack for cognitive Internet of Things

  • Wu, Jun;Wang, Cong;Yu, Yue;Song, Tiecheng;Hu, Jing
    • ETRI Journal
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    • 제42권6호
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    • pp.976-986
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    • 2020
  • Internet of Things (IoT) is considered the future network to support wireless communications. To realize an IoT network, sufficient spectrum should be allocated for the rapidly increasing IoT devices. Through cognitive radio, unlicensed IoT devices exploit cooperative spectrum sensing (CSS) to opportunistically access a licensed spectrum without causing harmful interference to licensed primary users (PUs), thereby effectively improving the spectrum utilization. However, an open access cognitive IoT allows abnormal IoT devices to undermine the CSS process. Herein, we first establish a hard-combining attack model according to the malicious behavior of falsifying sensing data. Subsequently, we propose a weighted sequential hypothesis test (WSHT) to increase the PU detection accuracy and decrease the sampling number, which comprises the data transmission status-trust evaluation mechanism, sensing data availability, and sequential hypothesis test. Finally, simulation results show that when various attacks are encountered, the requirements of the WSHT are less than those of the conventional WSHT for a better detection performance.