• 제목/요약/키워드: Order Statistics

검색결과 3,394건 처리시간 0.024초

NONINFORMATIVE PRIORS FOR LINEAR COMBINATION OF THE INDEPENDENT NORMAL MEANS

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Statistical Society
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    • 제33권2호
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    • pp.203-218
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    • 2004
  • In this paper, we develop the matching priors and the reference priors for linear combination of the means under the normal populations with equal variances. We prove that the matching priors are actually the second order matching priors and reveal that the second order matching priors match alternative coverage probabilities up to the second order (Mukerjee and Reid, 1999) and also, are HPD matching priors. It turns out that among all of the reference priors, one-at-a-time reference prior satisfies a second order matching criterion. Our simulation study indicates that one-at-a-time reference prior performs better than the other reference priors in terms of matching the target coverage probabilities in a frequentist sense. We compute Bayesian credible intervals for linear combination of the means based on the reference priors.

Bayesian Analysis for the Difference of Exponential Means

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제16권4호
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    • pp.1067-1078
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    • 2005
  • In this paper, we develop the noninformative priors for the exponential models when the parameter of interest is the difference of two means. We develop the first and second order matching priors. We reveal that the second order matching priors do not exist. It turns out that Jeffreys' prior does not satisfy the first order matching criterion. The Bayesian credible intervals based on the first order matching meet the frequentist target coverage probabilities much better than the frequentist intervals of Jeffreys' prior.

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Order Statistics를 적용한 Patchwork의 성능 개선 분석 (Performance Analysis of Order Statistics Patchwork)

  • 국효정;김용철
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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    • pp.163-166
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    • 2003
  • In conventional patchwork, the difference of the mean values of two groups is compared for watermark detection. We propose two modified patchwork schemes based on order statistics, which achieves significant improvements over conventional patchwork. First, we propose that the mean comparison is replaced by the median comparison, to get PSNR improvement due to informed watermarking. Second, we propose a majority voting scheme of a sequential comparison of pixel pairs in a sorted order, which produces significantly lower BER. The performance improvements are mathematically analyzed and tested. In experimental results, PSNR is about 5㏈~10㏈ higher in the first method and BER is about 1/5~l/2 times lower in the second method than conventional patchwork.

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SEMISYMMETRIC CUBIC GRAPHS OF ORDER 34p3

  • Darafsheh, Mohammad Reza;Shahsavaran, Mohsen
    • 대한수학회보
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    • 제57권3호
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    • pp.739-750
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    • 2020
  • A simple graph is called semisymmetric if it is regular and edge transitive but not vertex transitive. Let p be a prime. Folkman proved [J. Folkman, Regular line-symmetric graphs, Journal of Combinatorial Theory 3 (1967), no. 3, 215-232] that no semisymmetric graph of order 2p or 2p2 exists. In this paper an extension of his result in the case of cubic graphs of order 34p3, p ≠ 17, is obtained.

Selection of Canonical Factors in Second Order Response Surface Models

  • Park, Sung H.;Seong K. Han
    • Journal of the Korean Statistical Society
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    • 제30권4호
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    • pp.585-595
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    • 2001
  • A second-order response surface model is often used to approximate the relationship between a response factor and a set of explanatory factors. In this article, we deal with canonical analysis in response surface models. For the interpretation of the geometry of second-order response surface model, standard errors and confidence intervals for the eigenvalues of the second-order coefficient matrix play an important role. If the confidence interval for some eigenvalue includes 0 or the estimate of some eigenvalue is very small (near to 0) with respect to other eigenvalues, then we are able to delete the corresponding canonical factor. We propose a formulation of criterion which can be used to select canonical factors. This criterion is based on the IMSE(=Integrated Mean Squared Error). As a result of this method, we may approximately write the canonical factors as a set of some important explanatory factors.

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Slope-Rotatability over All Directions in Third Order Response Surface Models

  • Park, Sung-Hyun;Lee, Min-Soo
    • Journal of the Korean Statistical Society
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    • 제24권2호
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    • pp.519-536
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    • 1995
  • In the design of experiments for response surface analysis, sometimes it is of interest to estimate the difference of responses at two points. If differences at points close together are involved, the design that reliably estimates the slope of response surface is important. This idea was conceptualized by slope rotatability by Hader & Park (1978) and Park (1987). Until now, second order polynomial models were only studied for slope ratatability. In this paper, we will propose the necessary and sufficient conditions for slope rotatability over all directions for the thired order polynomial models in two, three and four independent variables. Also practical slope rotatable designs over all directions for two independent variables are suggested.

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Noninformative Priors for the Ratio of the Lognormal Means with Equal Variances

  • Lee, Seung-A;Kim, Dal-Ho
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.633-640
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    • 2007
  • We develop noninformative priors for the ratio of the lognormal means in equal variances case. The Jeffreys' prior and reference priors are derived. We find a first order matching prior and a second order matching prior. It turns out that Jeffreys' prior and all of the reference priors are first order matching priors and in particular, one-at-a-time reference prior is a second order matching prior. One-at-a-time reference prior meets very well the target coverage probabilities. We consider the bioequivalence problem. We calculate the posterior probabilities of the hypotheses and Bayes factors under Jeffreys' prior, reference prior and matching prior using a real-life example.

Relative Frequency of Order Statistics in Independent and Identically Distributed Random Vectors

  • Park, So-Ryoung;Kwon, Hyoung-Moon;Kim, Sun-Yong;Song, Iick-Ho
    • Communications for Statistical Applications and Methods
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    • 제13권2호
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    • pp.243-254
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    • 2006
  • The relative frequency of order statistics is investigated for independent and identically distributed (i.i.d.) random variables. Specifically, it is shown that the probability $Pr\{X_{[s]}=x\}$ is no less than the probability $Pr\{X_{[r]}=x\}$ at any point $x{\geqq}x_0$ when r$X_{[r]}$ denotes the r-th order statistic of an i.i.d. discrete random vector and $x_0$ depends on the population probability distribution. A similar result for i.i.d. continuous random vectors is also presented.

MODIFIED GEOMETRIC DISTRIBUTION OF ORDER k AND ITS APPLICATIONS

  • JUNGTAEK OH;KYEONG EUN LEE
    • Journal of applied mathematics & informatics
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    • 제42권3호
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    • pp.709-723
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    • 2024
  • We study the distributions of waiting times in variations of the geometric distribution of order k. Variation imposes length on the runs of successes and failures. We study two types of waiting time random variables. First, we consider the waiting time for a run of k consecutive successes the first time no sequence of consecutive k failures occurs prior, denoted by T(k). Next, we consider the waiting time for a run of k consecutive failures the first time no sequence of k consecutive successes occurred prior, denoted by J(k). In addition, we study the distribution of the weighted average. The exact formulae of the probability mass function, mean, and variance of distributions are also obtained.

PRELIMINARY DETECTION FOR ARCH-TYPE HETEROSCEDASTICITY IN A NONPARAMETRIC TIME SERIES REGRESSION MODEL

  • HWANG S. Y.;PARK CHEOLYONG;KIM TAE YOON;PARK BYEONG U.;LEE Y. K.
    • Journal of the Korean Statistical Society
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    • 제34권2호
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    • pp.161-172
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    • 2005
  • In this paper a nonparametric method is proposed for detecting conditionally heteroscedastic errors in a nonparametric time series regression model where the observation points are equally spaced on [0,1]. It turns out that the first-order sample autocorrelation of the squared residuals from the kernel regression estimates provides essential information. Illustrative simulation study is presented for diverse errors such as ARCH(1), GARCH(1,1) and threshold-ARCH(1) models.