• Title/Summary/Keyword: Distribution Department

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New Dispersion Function in the Rank Regression

  • Choi, Young-Hun
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.101-113
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    • 2002
  • In this paper we introduce a new score generating (unction for the rank regression in the linear regression model. The score function compares the $\gamma$'th and s\`th power of the tail probabilities of the underlying probability distribution. We show that the rank estimate asymptotically converges to a multivariate normal. further we derive the asymptotic Pitman relative efficiencies and the most efficient values of $\gamma$ and s under the symmetric distribution such as uniform, normal, cauchy and double exponential distributions and the asymmetric distribution such as exponential and lognormal distributions respectively.

Semi-parametric Bootstrap Confidence Intervals for High-Quantiles of Heavy-Tailed Distributions (꼬리가 두꺼운 분포의 고분위수에 대한 준모수적 붓스트랩 신뢰구간)

  • Kim, Ji-Hyun
    • Communications for Statistical Applications and Methods
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    • v.18 no.6
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    • pp.717-732
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    • 2011
  • We consider bootstrap confidence intervals for high quantiles of heavy-tailed distribution. A semi-parametric method is compared with the non-parametric and the parametric method through simulation study.

Bayesian Estimation of State-Space Model Using the Hybrid Monte Carlo within Gibbs Sampler

  • Park, Ilsu
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.203-210
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    • 2003
  • In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

Modelling on Multi-modal Circular Data using von Mises Mixture Distribution

  • Jang, Young-Mi;Yang, Dong-Yoon;Lee, Jin-Young;Na, Jong-Hwa
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.517-530
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    • 2007
  • We studied a modelling process for unimodal and multimodal circular data by using von Mises and its mixture distribution. In particular we suggested EM algorithm to find ML estimates of the mixture model. Simulation results showed the suggested methods are very accurate. Applications to two kinds of real data sets are also included.

Moments of a Class of Internally Truncated Normal Distributions

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.679-686
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    • 2007
  • Moment expressions are derived for the internally truncated normal distributions commonly applied to screening and constrained problems. They are obtained from using a recursive relation between the moments of the normal distribution whose distribution is truncated in its internal part. Closed form formulae for the moments can be presented up to $N^{th}$ order under the internally truncated case. Necessary theories and two applications are provided.

NEW LM TESTS FOR UNIT ROOTS IN SEASONAL AR PROCESSES

  • Oh, Yu-Jin;So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • v.36 no.4
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    • pp.447-456
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    • 2007
  • On the basis of marginal likelihood of the residual vector which is free of nuisance mean parameters, we propose new Lagrange Multiplier seasonal unit root tests in seasonal autoregressive process. The limiting null distribution of the tests is the standardized ${\chi}^2-distribution$. A Monte-Carlo simulation shows the new tests are more powerful than the tests based on the ordinary least squares (OLS) estimator, especially for large number of seasons and short time spans.

LIGHTLIKE SUBMANIFOLDS OF A SEMI-RIEMANNIAN MANIFOLD WITH A SEMI-SYMMETRIC NON-METRIC CONNECTION

  • Jin, Dae-Ho
    • The Pure and Applied Mathematics
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    • v.19 no.3
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    • pp.211-228
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    • 2012
  • We study lightlike submanifolds M of a semi-Riemannian manifold $\bar{M}$ with a semi-symmetric non-metric connection subject to the conditions; (a) the characteristic vector field of $\bar{M}$ is tangent to M, (b) the screen distribution on M is totally umbilical in M and (c) the co-screen distribution on M is conformal Killing.

Application of RFID -Centered around Distribution and Logistics Area- (RFID의 활용 -유통/물류 분야를 중심으로-)

  • Lee, Gong-Seop
    • Journal of the Korea Safety Management & Science
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    • v.12 no.4
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    • pp.161-168
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    • 2010
  • RFID has been used as an identification tool substituting bar-code and its application areas are increasing due to its suitability in ubiquitous environment. This paper reviews RFID applications in some areas in which a serious amount of applications were reported such as material handling, physical distribution, and supply chain management of perishable products. The authors try to suggest research issues along with the limitations of RFID.

A Test of Multivariate Normality Oriented for Testing Elliptical Symmetry

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.221-231
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    • 2006
  • A chi-squared test of multivariate normality is suggested which is oriented for detecting deviations from elliptical symmetry. We derive the limiting distribution of the test statistic via a central limit theorem on empirical processes. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under a non-normal distribution.

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A Simple Chi-Squared Test of Spherical Symmetry

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.2
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    • pp.227-236
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    • 2005
  • A chi-squared test of spherical symmetry is suggested. This test is easy to apply in practice since it is easy to compute and has a limiting chi-squared distribution under spherical symmetry. The result of Park(1998) can be used to show that it has the limiting chi-squared distribution. A simulation study is conducted to study the accuracy, in finite samples, of the limiting distribution. Finally, a simulation study that compares the power of our test with those of other tests of spherical symmetry is performed.

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