• 제목/요약/키워드: Confidence rate

검색결과 975건 처리시간 0.027초

Confidence intervals for the COVID-19 neutralizing antibody retention rate in the Korean population

  • Apio, Catherine;Kamruzzaman, Md.;Park, Taesung
    • Genomics & Informatics
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    • 제18권3호
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    • pp.31.1-31.8
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    • 2020
  • The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic. No specific therapeutic agents or vaccines for COVID-19 are available, though several antiviral drugs, are under investigation as treatment agents for COVID-19. The use of convalescent plasma transfusion that contain neutralizing antibodies for COVID-19 has become the major focus. This requires mass screening of populations for these antibodies. While several countries started reporting population based antibody rate, its simple point estimate may be misinterpreted without proper estimation of standard error and confidence intervals. In this paper, we review the importance of antibody studies and present the 95% confidence intervals COVID-19 antibody rate for the Korean population using two recently performed antibody tests in Korea. Due to the sparsity of data, the estimation of confidence interval is a big challenge. Thus, we consider several confidence intervals using Asymptotic, Exact and Bayesian estimation methods. In this article, we found that the Wald method gives the narrowest interval among all Asymptotic methods whereas mid p-value gives the narrowest among all Exact methods and Jeffrey's method gives the narrowest from Bayesian method. The most conservative 95% confidence interval estimation shows that as of 00:00 on September 15, 2020, at least 32,602 people were infected but not confirmed in Korea.

Quantile confidence region using highest density

  • Hong, Chong Sun;Yoo, Myung Soo
    • Communications for Statistical Applications and Methods
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    • 제26권1호
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    • pp.35-46
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    • 2019
  • Multivariate Confidence Region (MCR) cannot be used to obtain the confidence region of the mean vector of multivariate data when the normality assumption is not satisfied; however, the Quantile Confidence Region (QCR) could be used with a Multivariate Quantile Vector in these cases. The coverage rate of the QCR is better than MCR; however, it has a disadvantage because the QCR has a wide shape when the probability density function follows a bimodal form. In this study, we propose a Quantile Confidence Region using the Highest density (QCRHD) method with the Highest Density Region (HDR). The coverage rate of QCRHD was superior to MCR, but is found to be similar to QCR. The QCRHD is constructed as one region similar to QCR when the distance of the mean vector is close. When the distance of the mean vector is far, the QCR has one wide region, but the QCRHD has two smaller regions. Based on these features, it is found that the QCRHD can overcome the disadvantages of the QCR, which may have a wide shape.

APPROXIMATE CONFIDENCE LIMITS OF THE RELIABILITY PERFORMANCES FOR A COLD STANDBY SERIES SYSTEM

  • SHI YIMIN;SRI XIAOLIN;XU YONG
    • Journal of applied mathematics & informatics
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    • 제19권1_2호
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    • pp.439-445
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    • 2005
  • This paper is to investigate the approximate confidence limits of the reliability performances (such as failure rate, reliability function and average life) for a cold standby series system. The Bayesian approximate upper confidence limit of failure rate is obtained firstly, and next Bayesian approximate lower confidence limits for reliability function and average life are presented. The expressions for calculating Bayesian lower confidence limits of the reliability function and average life are also obtained, and an illustrative example is examined numerically by means of the Monte-Carlo simulation. Finally, the accuracy of confidence limits is discussed.

Multivariate confidence region using quantile vectors

  • Hong, Chong Sun;Kim, Hong Il
    • Communications for Statistical Applications and Methods
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    • 제24권6호
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    • pp.641-649
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    • 2017
  • Multivariate confidence regions were defined using a chi-square distribution function under a normal assumption and were represented with ellipse and ellipsoid types of bivariate and trivariate normal distribution functions. In this work, an alternative confidence region using the multivariate quantile vectors is proposed to define the normal distribution as well as any other distributions. These lower and upper bounds could be obtained using quantile vectors, and then the appropriate region between two bounds is referred to as the quantile confidence region. It notes that the upper and lower bounds of the bivariate and trivariate quantile confidence regions are represented as a curve and surface shapes, respectively. The quantile confidence region is obtained for various types of distribution functions that are both symmetric and asymmetric distribution functions. Then, its coverage rate is also calculated and compared. Therefore, we conclude that the quantile confidence region will be useful for the analysis of multivariate data, since it is found to have better coverage rates, even for asymmetric distributions.

Bootstrap confidence intervals for classification error rate in circular models when a block of observations is missing

  • Chung, Hie-Choon;Han, Chien-Pai
    • Journal of the Korean Data and Information Science Society
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    • 제20권4호
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    • pp.757-764
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    • 2009
  • In discriminant analysis, we consider a special pattern which contains a block of missing observations. We assume that the two populations are equally likely and the costs of misclassification are equal. In this situation, we consider the bootstrap confidence intervals of the error rate in the circular models when the covariance matrices are equal and not equal.

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Bootstrap Confidence Intervals of Classification Error Rate for a Block of Missing Observations

  • Chung, Hie-Choon
    • Communications for Statistical Applications and Methods
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    • 제16권4호
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    • pp.675-686
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    • 2009
  • In this paper, it will be assumed that there are two distinct populations which are multivariate normal with equal covariance matrix. We also assume that the two populations are equally likely and the costs of misclassification are equal. The classification rule depends on the situation when the training samples include missing values or not. We consider the bootstrap confidence intervals for classification error rate when a block of observation is missing.

Updated confidence intervals for the COVID-19 antibody retention rate in the Korean population

  • Kamruzzaman, Md.;Apio, Catherine;Park, Taesung
    • Genomics & Informatics
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    • 제18권4호
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    • pp.45.1-45.5
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    • 2020
  • With the ongoing rise of coronavirus disease 2019 (COVID-19) pandemic across the globe, interests in COVID-19 antibody testing, also known as a serology test has grown, as a way to measure how far the infection has spread in the population and to identify individuals who may be immune. Recently, many countries reported their population based antibody titer study results. South Korea recently reported their third antibody formation rate, where it divided the study between the general population and the young male youths in their early twenties. As previously stated, these simple point estimates may be misinterpreted without proper estimation of standard error and confidence intervals. In this article, we provide an updated 95% confidence intervals for COVID-19 antibody formation rate for the Korean population using asymptotic, exact and Bayesian statistical estimation methods. As before, we found that the Wald method gives the narrowest interval among all asymptotic methods whereas mid p-value gives the narrowest among all exact methods and Jeffrey's method gives the narrowest from Bayesian method. The most conservative 95% confidence interval estimation shows that as of 00:00 November 23, 2020, at least 69,524 people were infected but not confirmed. It also shows that more positive cases were found among the young male in their twenties (0.22%), three times that of the general public (0.051%). This thereby calls for the quarantine authorities' need to strengthen quarantine managements for the early twenties in order to find the hidden infected people in the population.

관측교통량의 통계적 분포에 의한 도로교통용량 산정 기법에 관한 연구 -이상적인 조건하의 고속도로 기본구간 대상- (The Development of Capacity Estimation Methods from Statistical Distribution of Observed Traffic Flow)

  • 김용걸;장명순
    • 대한교통학회지
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    • 제13권1호
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    • pp.167-183
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    • 1995
  • The objective of study is to evaluate highway capaicty estimation alternative and to develop capacity from statistical distribution of observed traffic flow. Speed-Volume relation is analyzed from vehicle's headway distribution eliminating the long headway by confidence intervals 99%, 95%, 90%. Capacity estimate alternatives were evaluated from 95% , 90%, 85% level of cummulative distribution of observed hourly traffic flow adjusted to confidence intervals. The result of investigation revealed that maximum hourly rate of flow is 2, 130pcu at confidence interval of 995, 2, 233pcu at 95%, 2, 315pcu at 90% respectively. Compared to the capacity of 2, 200pcu per hour per lane used in HCM and KHCM(Korea Highway Capacity Manual), capa챠y appears to correspond to confidence interval of 95%. Using the traffic flow rate at confidence interval of 95% the maximum hourly flow rate is 2, 187pcu at 95% of cummulative volume distribution, 2, 153pcu at 90%, 2, 215pcu at 85%. The study suggests that raional capacity esimation alternative is to take the 95% of cummulative distribution of observed hourly traffic flow at 95% confidence headway interval eliminating 5% long headway.(i.e. 95-95 rule)

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경제위기시 환율신뢰구간 예측 알고리즘 개발 (Confidence interval forecast of exchange rate based on bootstrap method during economic crisis)

  • 김태윤;권오진
    • Journal of the Korean Data and Information Science Society
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    • 제22권5호
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    • pp.895-902
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    • 2011
  • 본 연구는 경제위기시 환율의 신뢰구간 예측 알고리즘을 개발하는 것을 주된 목적으로 한다. 경제위기시 환율의 움직임의 특징은 평상시에 비해 변동성이 극도로 증가한다는 점이다. 본 연구에서는 이러한 변동성을 효율적으로 추정하기 위해 시계열 데이터의 변동성 추정에 유용한 것으로 알려진 블록 붓스트랩 기법을 사용하여 그 유용성을 보인다.

붓스트랩 기법을 이용한 환율의 장단기 신뢰구간 예측 (Confidence interval forecast of exchange rate based on bootstrap method)

  • 권오진;김태윤;송규문
    • Journal of the Korean Data and Information Science Society
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    • 제21권3호
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    • pp.493-502
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    • 2010
  • 환율의 신뢰구간을 예측하기 위해 가장 중요한 요인은 분포의 추정이다. 그러나 시계열 자료의 분포를 추정하는 것은 많은 어려움이 따른다. 본 연구에서는 변동률 합의 분포를 비모수기법 중의 하나인 블록화 붓스트랩 방법을 사용하여 추정한다. 따라서 좀 더 쉽고 정확한 환율의 장단기 신뢰구간 예측 모형을 제시한다.