• 제목/요약/키워드: two sample testing

검색결과 249건 처리시간 0.027초

A Bayesian Multiple Testing of Detecting Differentially Expressed Genes in Two-sample Comparison Problem

  • Oh Hyun-Sook;Yang Wan-Youn
    • Communications for Statistical Applications and Methods
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    • 제13권1호
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    • pp.39-47
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    • 2006
  • The Bayesian approach to multiple testing procedure for one sample testing problem proposed by Scott and Berger (2003) is extended to two-sample comparison problem in microarray experiments. The prior distribution of each gene's mean for one sample is given conditionally on the corresponding gene's mean for the other sample. Posterior distributions of interesting parameters are derived and estimated based on an importance sampling method. A simulated example is given for illustration.

이단계 그룹검사를 갖는 대기행렬모형의 분석 (Analysis of a Queueing Model with a Two-stage Group-testing Policy)

  • 양원석
    • 산업경영시스템학회지
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    • 제45권4호
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    • pp.53-60
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    • 2022
  • In a group-testing method, instead of testing a sample, for example, blood individually, a batch of samples are pooled and tested simultaneously. If the pooled test is positive (or defective), each sample is tested individually. However, if negative (or good), the test is terminated at one pooled test because all samples in the batch are negative. This paper considers a queueing system with a two-stage group-testing policy. Samples arrive at the system according to a Poisson process. The system has a single server which starts a two-stage group test in a batch whenever the number of samples in the system reaches exactly a predetermined size. In the first stage, samples are pooled and tested simultaneously. If the pooled test is negative, the test is terminated. However, if positive, the samples are divided into two equally sized subgroups and each subgroup is applied to a group test in the second stage, respectively. The server performs pooled tests and individual tests sequentially. The testing time of a sample and a batch follow general distributions, respectively. In this paper, we derive the steady-state probability generating function of the system size at an arbitrary time, applying a bulk queuing model. In addition, we present queuing performance metrics such as the offered load, output rate, allowable input rate, and mean waiting time. In numerical examples with various prevalence rates, we show that the second-stage group-testing system can be more efficient than a one-stage group-testing system or an individual-testing system in terms of the allowable input rates and the waiting time. The two-stage group-testing system considered in this paper is very simple, so it is expected to be applicable in the field of COVID-19.

Large Sample Test for Independence in the Bivariate Pareto Model with Censored Data

  • Cho, Jang-Sik;Lee, Jea-Man;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제14권2호
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    • pp.377-383
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    • 2003
  • In this paper, we consider two components system in which the lifetimes follow the bivariate Pareto model with random censored data. We assume that the censoring time is independent of the lifetimes of the two components. We develop large sample tests for testing independence between two components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

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MINITAB Macros for Testing the Difference of Mean Vectors of Two Multivariate Populations

  • Hyuk Joo;Min Ah
    • Communications for Statistical Applications and Methods
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    • 제7권1호
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    • pp.179-198
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    • 2000
  • We consider the problem of comparing the mean vectors of two multivaiate populations, We focus on testing hypotheses concerning two multivariate mean vectors by use of MINITAB, For the cases of small sample and large sample MINITAB programs and outputs are presented for solving staistical problems. The MiniTAB programs made in this paper are saved as macro files and thus can be conveniently used for solving another problems.

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ON TESTING THE EQUALITY OF THE COEFFICIENTS OF VARIATION IN TWO INVERSE GAUSSIAN POPULATIONS

  • Choi, Byung-Jin;Kim, Kee-Young
    • Journal of the Korean Statistical Society
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    • 제32권2호
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    • pp.93-101
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    • 2003
  • This paper deals with testing the equality of the coefficients of variation in two inverse Gaussian populations. The likelihood ratio, Lagrange-multiplier and Wald tests are presented. Monte-Carlo simulations are performed to compare the powers of these tests. In a simulation study, the likelihood ratio test appears to be consistently more powerful than the Lagrange-multiplier and Wald tests when sample size is small. The powers of all the tests tend to be similar when sample size increases.

Large Sample Tests for Independence in Bivariate Pareto Model with Censored Data

  • 조장식;이재만;이우동
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2003년도 춘계학술대회
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    • pp.121-126
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    • 2003
  • In this paper, we consider two-components system which the lifetimes follow bivariate pareto model with censored data. We develop large sample tests for testing independence between two-components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

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A Bayes Criterion for Testing Homogeneity of Two Multivariate Normal Covariances

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • 제27권1호
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    • pp.11-23
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    • 1998
  • A Bayes criterion for testing the equality of covariance matrices of two multivariate normal distributions is proposed and studied. Development of the criterion invloves calculation of Bayes factor using the imaginary sample method introduced by Spiegelhalter and Smith (1982). The criterion is designed to develop a Bayesian test criterion, so that it provides an alternative test criterion to those based upon asymptotic sampling theory (such as Box's M test criterion). For the constructed criterion, numerical studies demonstrate routine application and give comparisons with the traditional test criteria.

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A Two Sample Test for Functional Data

  • Lee, Jong Soo;Cox, Dennis D.;Follen, Michele
    • Communications for Statistical Applications and Methods
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    • 제22권2호
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    • pp.121-135
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    • 2015
  • We consider testing equality of mean functions from two samples of functional data. A novel test based on the adaptive Neyman methodology applied to the Hotelling's T-squared statistic is proposed. Under the enlarged null hypothesis that the distributions of the two populations are the same, randomization methods are proposed to find a null distribution which gives accurate significance levels. An extensive simulation study is presented which shows that the proposed test works very well in comparison with several other methods under a variety of alternatives and is one of the best methods for all alternatives, whereas the other methods all show weak power at some alternatives. An application to a real-world data set demonstrates the applicability of the method.

Probability of Rejection Curve for Equivalence Testing Procedure

  • Sung, Nae Kyung
    • 품질경영학회지
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    • 제22권4호
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    • pp.102-110
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    • 1994
  • We investigate the small-sample behavior of the probability of rejection curves and its performance for a equivalence testing procedure based on confidence intervals which was developed with a motivation from bioequivalence studies. This type of equivalence studies are conducted frequently in pharmaceutical industries to compare the relative bioavailabilty of two formulations of a drug and can be applied various fields where assurance of quality equivalence is needed. From the Monte-Carlo simulation results we suggest proper sample sizes for the equivalence testing procedure.

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두개의 공분산 행렬의 동질성 검정에서의 영향치 분석 (Influence in Testing the Equality of Two Covariance Matrices)

  • Myung Geun Kim
    • 응용통계연구
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    • 제7권2호
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    • pp.213-224
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    • 1994
  • 두개의 공분산 행렬의 동질성을 검정하는데 있어서, influence curve 방법을 이용하여 outlier를 찾는데 유용한 진단법을 제시한다. 이러한 진단법은 두개 이상의 공분산 행렬의 경우에 쉽게 일반화된다. 경험적 분포함수에 입각한 진단법의 sample version을 고려하며, 이것은 Wilks가 제안한 한개의 outlier를 찾는데 필요한 통계량과 두개의 모집단의 경우로 일반화된 Wilks 통계량을 포함한다.

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