• Title/Summary/Keyword: Projection Statistics

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A simulation study on projection pursuit discriminant analysis (투사지향방법에 의한 판별분석의 모의실험분석)

  • 안윤기;이성석
    • The Korean Journal of Applied Statistics
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    • v.5 no.1
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    • pp.103-111
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    • 1992
  • The projection pursuit method has been gussested as a technique for the analysis of the multivariate data. This method seeks out interesting linear projections of the multivariate data onto a line of a plane to solve the curse or dimensionality. In this paper we developed the discriminant analysis by using the projection method and simulations were used for comparison between this and other existing discriminant analysis methods.

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Projection Pursuit K-Means Visual Clustering

  • Kim, Mi-Kyung;Huh, Myung-Hoe
    • Journal of the Korean Statistical Society
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    • v.31 no.4
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    • pp.519-532
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    • 2002
  • K-means clustering is a well-known partitioning method of multivariate observations. Recently, the method is implemented broadly in data mining softwares due to its computational efficiency in handling large data sets. However, it does not yield a suitable visual display of multivariate observations that is important especially in exploratory stage of data analysis. The aim of this study is to develop a K-means clustering method that enables visual display of multivariate observations in a low-dimensional space, for which the projection pursuit method is adopted. We propose a computationally inexpensive and reliable algorithm and provide two numerical examples.

An improvement of estimators for the multinormal mean vector with the known norm

  • Kim, Jaehyun;Baek, Hoh Yoo
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.435-442
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    • 2017
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}$ (p ${\geq}$ 3) under the quadratic loss from multi-variate normal population. We find a James-Stein type estimator which shrinks towards the projection vectors when the underlying distribution is that of a variance mixture of normals. In this case, the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is known where K is a projection vector with rank(K) = q. The class of this type estimator is quite general to include the class of the estimators proposed by Merchand and Giri (1993). We can derive the class and obtain the optimal type estimator. Also, this research can be applied to the simple and multiple regression model in the case of rank(K) ${\geq}2$.

A Study on Projection Properties of the 12-Run Plackett-Burman Design

  • Park, Dong-Kwon
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.707-718
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    • 1999
  • Non-regular designs such as the Plackett-Burman(PB) design have traditionally been used for screening only main effects because of complex aliasing. But it was found that these designs could be used to estimate the 2-factor interactions as well as main effects through the hidden projection property. The goal of this paper is to propose the estimable model when projecting the 12-run PB design using the algebraic geometric method. The core of this method considers the design as a affine variety and the Grbner basis of the design ideal for this affine variety gives the estimable polynomial models. As the results of applying the 12-run PB design it is actually found that this design has the models not only with 2-factor interactions but with 3-factor. This design is the maximal fan in 4-factor projection.

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CONVERGENCE OF WEIGHTED U-EMPIRICAL PROCESSES

  • Park, Hyo-Il;Na, Jong-Hwa
    • Journal of the Korean Statistical Society
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    • v.33 no.4
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    • pp.353-365
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    • 2004
  • In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

Modifcation of Reconstruction Filter for Low-Dose Reconstruction (저조사광 재구성을 위한 필터 설계)

  • 염영호
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.17 no.1
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    • pp.23-30
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    • 1980
  • The reconstruction problem in a low dose case requires some compromise of resolution and noise artifacts, and also some modification of filter kernels depending on the signal-to-noise ratio of projection data. In this paper, ail algorithm for the reconstruction of an image function from noisy projection data is suggested, based on minimum-mean-square error criterion. Modification of the falter kernel is made from information (statistics) obtained from the projection data. The simulation study Proves that this algorithm, based on the Wiener falter approach, provides substantially improved image with reduction of noise as well as improvement of the resolution. An approximate method was also studied which leads to the possible use of a recursive filter in the convolution process of image reconstruction.

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A Quasi-Likelihood Approach to Nonlinear Filtering Problems

  • Kim, Yoon-Tae
    • Journal of the Korean Statistical Society
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    • v.27 no.2
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    • pp.221-235
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    • 1998
  • Suppose that an observed process can be written as the additive model of the signal process and the noise process with unknown parameters. In practice the signal process is not directly observed. We consider the problem of estimating parameter from the observation process using the quasi-likelihood method.

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Projected Circular and l-Axial Skew-Normal Distributions

  • Seo, Han-Son;Shin, Jong-Kyun;Kim, Hyoung-Moon
    • The Korean Journal of Applied Statistics
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    • v.22 no.4
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    • pp.879-891
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    • 2009
  • We developed the projected l-axial skew-normal(LASN) family of distributions for I-axial data. The LASN family of distributions contains the semicircular skew-normal(SCSN) and the circular skew-normal(CSN) families of distributions as special cases. The LASN densities are similar to the wrapped skew-normal densities for the small values of the scale parameter. However CSN densities have more heavy tails than those of the wrapped skew-normal densities on the circle. Furthermore the CSN densities have two modes as the scale parameter increases. The LASN distribution has very convenient mathematical features. We extend the LASN family of distributions to a bivariate case.

Benefit-Cost Analysis and Sustainability of National Pension (국민연금의 수급부담구조분석과 지속가능성)

  • Kim, Seongyong;Bang, Junho;Park, Yousung
    • The Korean Journal of Applied Statistics
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    • v.28 no.4
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    • pp.603-620
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    • 2015
  • The National Pension of Korea is a public social security system designed to alleviate social risks and poverty that has had a major impact on the quality of life for the aging population. However, a rapidly aging population and low fertility threaten the sustainability of national pension in Korea. The National Pension Research Institute publishes a nancial projection every ve years; consequently, the government has lowered the entitlements for the sustainability of national pension based on the projection results. The current reform of the pension system that arbitrarily reduces the entitlements might detract from the income security role of the national pension for pensioners without accounting for the highest elderly poverty rate in the OECD countries. We first discuss methods for the financial projection of the national pension in terms of population, subscribers, and pensioner projections in order to estimate the pension reserve fund and the financial depletion year. We also conduct a sensitivity analysis for population variables, institutional variables, and economic variables based on pension reserves and the financial depletion year. We evaluate intergenerational fairness between the income hierarchy by conducting a money's worth analysis. Finally, we investigate the possibility of the sustainability of national pension by adjusting pension contributions and entitlements (income replacement rate). A new dependency ratio shows that a simple reform of the national pension does not secure the sustainability of the national pension without adapting a pay-as-you-go system.