• Title/Summary/Keyword: Correlated sampling

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Design of a CMOS Image Sensor Based on a 10-bit Two-Step Single-Slope ADC (10-bit Two-Step Single Slope A/D 변환기를 이용한 고속 CMOS Image Sensor의 설계)

  • Hwang, Inkyung;Kim, Daeyun;Song, Minkyu
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.11
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    • pp.64-69
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    • 2013
  • In this paper, a high-speed CMOS Image Sensor (CIS) based on a 10-bit two-step single-slope A/D converter is proposed. The A/D converter is composed of both a 5-bit coarse ADC and a 6-bit fine ADC, and the conversion speed is 10 times faster than that of the single-slope A/D converter. In order to have a small noise characteristics, further, a Digital Correlated Double Sampling(D-CDS) is also discussed. The proposed A/D converter has been fabricated with 0.13um 1-poly 4-metal CIS process, and it has a QVGA($320{\times}240$) resolution. The fabricated chip size is $5mm{\times}3mm$, and the power consumption is about 35mW at 3.3V supply voltage. The measured conversion speed is 10us, and the frame rate is 220 frames/s.

Switching properties of CUSUM charts for controlling mean vector

  • Chang, Duk-Joon;Heo, Sun-Yeong
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.859-866
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    • 2012
  • Some switching properties of multivariate control charts are investigated when the interval between two consecutive sample selections is not fixed but changes according to the result of the previous sample observation. Many articles showed that the performances of variable sampling interval control charts are more efficient than those of fixed sampling interval control charts in terms of average run length (ARL) and average time to signal (ATS). Unfortunately, the ARL and the ATS do not provide any information on how frequent a switch is being made. We evaluate several switching properties of two sampling interval Shewhart and CUSUM procedures for controlling mean vector of correlated quality variables.

Multivariate Rotation Design for Population Mean in Sampling on Successive Occasions

  • Priyanka, Kumari;Mittal, Richa;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.445-462
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    • 2015
  • This article deals with the problem of estimation of the population mean in presence of multi-auxiliary information in two occasion rotation sampling. A multivariate exponential ratio type estimator has been proposed to estimate population mean at current (second) occasion using information on p-additional auxiliary variates which are positively correlated to study variates. The theoretical properties of the proposed estimator are investigated along with the discussion of optimum replacement strategies. The worthiness of proposed estimator has been justified by comparing it to well-known recent estimators that exist in the literature of rotation sampling. Theoretical results are justified through empirical investigations and a detailed study has been done by taking different choices of the correlation coefficients. A simulation study has been conducted to show the practicability of the proposed estimator.

A Sampling Design on the Survey of Non-Consignment Fishery Products (水산物 非系統생산量 調査에 關한 標本設計)

  • 朴弘來
    • Journal of the Korean Statistical Society
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    • v.9 no.2
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    • pp.213-217
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    • 1980
  • This paper aimed at studying an efficient sampling design of the survey for non-consignment fishery products including both marine fisheries and seaculture. An analysis was done on the relationship between precision and sample size. On the basis of the analysis, the sample size was determined to be 1,080 fishery house holds with the expected precision of 4%-5%. The molluscs and seaculture were recognized to be correlated with the non-consignment products. An attempt was made to investigate the coverage of the fish kinds by the sample about 100 fish kinds were found in the 80 selected sample villages, whereas the population includes about 120 in total. This shows that the sample represents the population with satisfaction.

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A Statistical Control Chart for Process with Correlated Subgroups

  • Lee, Kwang-Ho
    • Communications for Statistical Applications and Methods
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    • v.5 no.2
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    • pp.373-381
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    • 1998
  • In this paper a new control chart which accounts for correlation between process subgroups will be proposed. We consider the case where the process fluctuations are autocorrelated by a stationary AR(1) time series and where n($\geq1$) items are sampled from the process at each sampling time. A simulation study is presented and shows that for correlated subgroups, the proposed control chart makes a significant improvement over the traditionally employed X-bar chart which ignores subgroup correlations. Finally, we illustrate the proposed chart by comparing the standardized residuals and X-bar chart on a data set of motor shaft diameters.

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Bayesian Parameter :Estimation and Variable Selection in Random Effects Generalised Linear Models for Count Data

  • Oh, Man-Suk;Park, Tae-Sung
    • Journal of the Korean Statistical Society
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    • v.31 no.1
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    • pp.93-107
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    • 2002
  • Random effects generalised linear models are useful for analysing clustered count data in which responses are usually correlated. We propose a Bayesian approach to parameter estimation and variable selection in random effects generalised linear models for count data. A simple Gibbs sampling algorithm for parameter estimation is presented and a simple and efficient variable selection is done by using the Gibbs outputs. An illustrative example is provided.

Economic Design of Variable Sampling Interval X Control Chart Using a Surrogate Variable (대용변수를 이용한 가변형 부분군 채취 간격 X 관리도의 경제적 설계)

  • Lee, Tae-Hoon;Lee, Jooho;Lee, Minkoo
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.5
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    • pp.422-428
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    • 2013
  • In many cases, an $\bar{X}$ control chart which is based on the performance variable is used in industrial fields. However, if the performance variable is too costly or impossible to measure and a less expensive surrogate variable is available, the process may be more efficiently controlled using surrogate variables. In this paper, we propose a model for the economic design of a VSI (Variable Sampling Interval) $\bar{X}$ control chart using a surrogate variable that is linearly correlated with the performance variable. The total average profit model is constructed, which involves the profit per cycle time, the cost of sampling and testing, the cost of detecting and eliminating an assignable cause, and the cost associated with production during out-of-control state. The VSI $\bar{X}$ control charts using surrogate variables are expected to be superior to the Shewhart FSI (Fixed Sampling Interval) $\bar{X}$ control charts using surrogate variables with respect to the expected profit per unit cycle time from economic viewpoint.

A comparison of alternative estimators in view of the Rao-Hartley-Cochran sampling scheme

  • Hong, Ki-Hak;Lee, Gi-Sung;Son, Chang-Kyoon
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.181-187
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    • 2006
  • In this paper we suggest a new alternative estimator for the characteristics that are pooly correlated with the selection probabilities by applying the Amahia et al.(1989)'s estimator to Rao-Hartley-Cochran sampling scheme and compare it with that of Rao(1966)'s under a super-population model.

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Comparison of EWMA and CUSUM Charts with Variable Sampling Intervals for Monitoring Variance-Covariance Matrix

  • Chang, Duk-Joon
    • Journal of Integrative Natural Science
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    • v.13 no.4
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    • pp.152-157
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    • 2020
  • To monitor all elements simultaneously of variance-covariance matrix Σ of several correlated quality characteristics under multivariate normal process Np($\underline{\mu}$, Σ), multivariate exponentially weighted moving average (EWMA) chart and cumulative sum (CUSUM) chart are considered and compared. Numerical performances of the considered variable sampling interval (VSI) charts are evaluated using average run length (ARL), average time to signal (ATS), average number of switches (ANSW) to signal, and the probability of switch Pr(switch) between two sampling interval d1 and d2 where d1 < d2. For small or moderate changes of Σ, the performances of multivariate EWMA chart is approximately equivalent to that of multivariate CUSUM chart.

Investigation of Biases for Variance Components on Multiple Traits with Varying Number of Categories in Threshold Models Using Bayesian Inferences

  • Lee, D.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.15 no.7
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    • pp.925-931
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    • 2002
  • Gibbs sampling algorithms were implemented to the multi-trait threshold animal models with any combinations of multiple binary, ordered categorical, and linear traits and investigate the amount of bias on these models with two kinds of parameterization and algorithms for generating underlying liabilities. Statistical models which included additive genetic and residual effects as random and contemporary group effects as fixed were considered on the models using simulated data. The fully conditional posterior means of heritabilities and genetic (residual) correlations were calculated from 1,000 samples retained every 10th samples after 15,000 samples discarded as "burn-in" period. Under the models considered, several combinations of three traits with binary, multiple ordered categories, and continuous were analyzed. Five replicates were carried out. Estimates for heritabilities and genetic (residual) correlations as the posterior means were unbiased when underlying liabilities for a categorical trait were generated given by underlying liabilities of the other traits and threshold estimates were rescaled. Otherwise, when parameterizing threshold of zero and residual variance of one for binary traits, heritability estimates were inflated 7-10% upward. Genetic correlation estimates were biased upward if positively correlated and downward if negatively correlated when underling liabilities were generated without accounting for correlated traits on prior information. Residual correlation estimates were, consequently, much biased downward if positively correlated and upward if negatively correlated in that case. The more categorical trait had categories, the better mixing rate was shown.