• Title/Summary/Keyword: Minimum sampling

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The Role of Negative Binomial Sampling In Determining the Distribution of Minimum Chi-Square

  • Hamdy H.I.;Bentil Daniel E.;Son M.S.
    • International Journal of Contents
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    • v.3 no.1
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    • pp.1-8
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    • 2007
  • The distributions of the minimum correlated F-variable arises in many applied statistical problems including simultaneous analysis of variance (SANOVA), equality of variance, selection and ranking populations, and reliability analysis. In this paper, negative binomial sampling technique is employed to derive the distributions of the minimum of chi-square variables and hence the distributions of the minimum correlated F-variables. The work presented in this paper is divided in two parts. The first part is devoted to develop some combinatorial identities arised from the negative binomial sampling. These identities are constructed and justified to serve important purpose, when we deal with these distributions or their characteristics. Other important results including cumulants and moments of these distributions are also given in somewhat simple forms. Second, the distributions of minimum, chisquare variable and hence the distribution of the minimum correlated F-variables are then derived within the negative binomial sampling framework. Although, multinomial theory applied to order statistics and standard transformation techniques can be used to derive these distributions, the negative binomial sampling approach provides more information regarding the nature of the relationship between the sampling vehicle and the probability distributions of these functions of chi-square variables. We also provide an algorithm to compute the percentage points of the distributions. The computation methods we adopted are exact and no interpolations are involved.

A Study on the Determination of a Minimum Cost Sampling Inspection Plan for Destructive Testing (파괴검사(破壞檢査)에 있어서의 최소비용(最少費用) 샘플링 검사방식(檢査方式)의 결정(決定)에 관한 연구(硏究) - 계수파괴(計數破壞) 1회검사(回檢査)를 중심(中心)으로 -)

  • Hwang, Ui-Cheol;Jeong, Yeong-Bae
    • Journal of Korean Society for Quality Management
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    • v.8 no.2
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    • pp.15-22
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    • 1980
  • This paper deals with the problem of determining a minimum cost sampling inspection plan for a single destructive testing by attribute. The cost for inspection lot is constructed by following three cost factors: (1) cost of inspection, (2) cost of accepted defective, (3) cost of rejected lot Using Hald's Bayesian approach in a single non-destructive testing, procedure's for finding the minimum cost single destructive sampling inspection plan by attribute are given. Assuming the uniform distribution as a prior-distribution and using numerical analysis by computer, a minimum cost single destructive sampling inspection plan by attribute for several lot sizes, unit cost, destructive testing cost, and salvage cost is given.

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A Searching Algorithm for Minimum Bandpass Sampling Frequency in Simultaneous Down-Conversion of Multiple RF Signals

  • Bae, Jung-Hwa;Park, Jin-Woo
    • Journal of Communications and Networks
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    • v.10 no.1
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    • pp.55-62
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    • 2008
  • Bandpass sampling (BPS) techniques for the direct down-conversion of RF bandpass signals have become an essential technique for software defined radio (SDR), due to their advantage of minimizing the radio frequency (RF) front-end hardware dependency. This paper proposes an algorithm for finding the minimum BPS frequency for simultaneously down-converting multiple RF signals through full permutation over all the valid sampling ranges found for the multiple RF signals. We also present a scheme for reducing the computational complexity resulting from the large scale of the purmutation calculation involved in searching for the minimum BPS frequency. In addition, we investigate the BPS frequency allowing for the guard-band between adajacent down-converted signals, which help lessen the severe requirements in practical implementations. The performance of the proposed method is compared with those of other pre-reported methods to prove its effectiveness.

A Simple Proposition for Improving Industrial Hygiene Air Sampling Methods

  • Paik, Samuel Y.;Zalk, David M.
    • Safety and Health at Work
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    • v.10 no.3
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    • pp.389-392
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    • 2019
  • When conducting an exposure assessment, the primary goal of the industrial hygienist is to fully characterize the worker's exposure during a work shift to compare it with an occupational exposure limit. This applies regardless of the duration of the work activity as an activity that is relatively short in duration can still present exposure in excess of the occupational exposure limit even when normalized over an 8-hr shift. This goal, however, is often impeded by the specification of a minimum sample volume in the published sampling method, which may prevent the sample from being collected or submitted for analysis. Removing the specification of minimum sample volume (or adjusting it from a requirement to a recommendation), in contrast, allows for a broader assessment of jobs that consist of short-duration and high-exposure activities and also eliminates the unnecessary practice of running sampling pumps in clean air to collect a specified, minimum volume.

Randomized Response Model with Discrete Quantitative Attribute by Three-Stage Cluster Sampling

  • Lee, Gi-Sung;Hong, Ki-Hak
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.1067-1082
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    • 2003
  • In this paper, we propose a randomized response model with discrete quantitative attribute by three-stage cluster sampling for obtaining discrete quantitative data by using the Liu & Chow model(1976), when the population was made up of sensitive discrete quantitative clusters. We obtain the minimum variance by calculating the optimum number of fsu, ssu, tsu under the some given constant cost. And we obtain the minimum cost under the some given accuracy.

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Nonparametric confidence intervals for quantiles based on a modified ranked set sampling

  • Morabbi, Hakime;Razmkhah, Mostafa;Ahmadi, Jafar
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.119-129
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    • 2016
  • A new sampling method is introduced based on the idea of a ranked set sampling scheme in which taken samples in each set are dependent on previous ones. Some theoretical results are presented and distribution-free confidence intervals are derived for the quantiles of any continuous population. It is shown numerically that the proposed sampling scheme may lead to 95% confidence intervals (especially for extreme quantiles) that cannot be found based on the ordinary ranked set sampling scheme presented by Chen (2000) and Balakrishnan and Li (2006). Optimality aspects of this scheme are investigated for both coverage probability and minimum expected length criteria. A real data set is also used to illustrate the proposed procedure. Conclusions are eventually stated.

A Complex Bandpass Sampling Method for Downconversion of Multiple Bandpass Signals (다중 대역통과 신호의 하향변환을 위한 Complex Bandpass Sampling 기법)

  • Bae, Jung-Hwa;Ha, Won;Park, Jin-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.9C
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    • pp.913-921
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    • 2005
  • A complex bandpass sampling technique can provide a more flexible architecture for designing a software- defined radio(SDR) system, because it has several advantageous features of larger sampling range and lower minimum sampling frequency than a real bandpass sampling method. In spite of the potential advantages of the complex bandpass sampling, solid investigation for the direct downconversion of multiple signals by the complex sampling theory has not been reported yet. Thus, we propose in this paper a novel scheme for the downconversion of multiple signals using the complex bandpass sampling, and develop the formulae related to the complex bandpass sampling for practical usage, such as the valid sampling range, the intermediate frequency (If), and the minimum sampling frequency of the downconversion of multiple RE signals. Such derived formulae are verified from simulations.

A minimum cost sampling inspection plan for destructive testing (破壤檢査詩의 最小費용 샘플링 檢査方式)

  • 趙星九;裵道善
    • Journal of the Korean Statistical Society
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    • v.7 no.1
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    • pp.27-43
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    • 1978
  • This paper deals with the problem of obtaining a minimum cost acceptance sampling plan for destructive testing. The cost model is constructed under the assumption that the sampling procedure takes the following form; 1) lots rejected on the first sample are acreened with a non-destructive testing, 2) the screening is assumed to be imperfect, and therefore, after the screening, a second sample is taken to determine whether to accept the lot of to scrap it. The usual sampling procedures for destructive testing can be regarded as special cases of the above one. Utilizing Hald's Bayesian approach, procedures for finding the global optimal sampling plans are given. However, when the lot size is large, the global plan is very different to obtain even with the aid of an electronic computer. Therefore a method of finding suboptimal plan is suggested. An example with uniform prior is also given.

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On the Estimation of Fraction Defectives

  • Kim, Seong-in
    • Journal of Korean Society for Quality Management
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    • v.8 no.2
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    • pp.3-14
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    • 1980
  • This paper is concerned with the design of an appropriate sampling plan or stopping rule and the construction of estimate for the estimation of process or lot fraction defective. Various sampling plans which are well known or have potential applications are unified into a generalized sampling plan. Under this sampling plan sufficient statistic, probability distribution, moment, and minimum variance unbiased estimate are obtained. Results for various sampling plans can be derived as special cases. Then, under given parameter values, the relative efficiencies of the various sampling plans are compared with respect to expected sample sizes and variances of estimates.

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Regression Estimators with Unequal Selection Probabilities on Two Successive Occasions

  • Kim, Kyu-Seong
    • Journal of the Korean Statistical Society
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    • v.25 no.1
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    • pp.25-37
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    • 1996
  • In this paper, we propose regression estimators based on a partial replacement sampling scheme over two successive occasions and derive the minimum variances of them. PPSWR, RHC, $\pi$PS and PPSWOR schemes are considered to select unequal probability samples on two occasions. Simulation results over four populations are given for comparison of composite estimators and regression estimators.

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