• Title/Summary/Keyword: Resampling

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On the Equality of Two Distributions Based on Nonparametric Kernel Density Estimator

  • Kim, Dae-Hak;Oh, Kwang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.247-255
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    • 2003
  • Hypothesis testing for the equality of two distributions were considered. Nonparametric kernel density estimates were used for testing equality of distributions. Cross-validatory choice of bandwidth was used in the kernel density estimation. Sampling distribution of considered test statistic were developed by resampling method, called the bootstrap. Small sample Monte Carlo simulation were conducted. Empirical power of considered tests were compared for variety distributions.

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Development of Web-based Statistical System for Bootstrap on the Internet Environment (인터넷 환경에서 붓스트랩 통계 시스템의 개발)

  • 최성운;임인섭
    • Journal of the Korea Safety Management & Science
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    • v.6 no.2
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    • pp.241-250
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    • 2004
  • Recently, growth of internet causes rapid changes in many areas of statistics such as statistical computation and education. Especially, bootstrap is the most interesting statistical methods applying computer resampling simulation. In this study, we try to present how to use a method of bootstrap on the internet. We also develop to user a statistical system which is programed with java applet for user to handle easily.

Rank Reduction for Wideband Signals incident on a Uniform Linear Array

  • Hong, Wooyoung
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1992.06a
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    • pp.123-126
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    • 1992
  • A new class of data transformation matri is introduced for estimation of angles of arrivals by the rank reduction of multiple wideband sources. The proposed unitary focusing matri minimizes the average of the squared norm of focusing error over the angles of interest without a priori knowledge of source locations. The merit that result as a consequence is a lower resolution threshold. These matrices can be applied to the case of the multigroup sources. Simulations and the comparison of statistical performance are compared with the algorithms (especially, spatial resampling method) which does not require the pre-estimation.

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Development of High Performance Dynamic System Monitor for Dynamic Modeling and Disturbance Monitoring (다이나믹 모델링 및 외란감시를 위한 고성능 Dynamic System Monitor 장비 개발)

  • Kim, D.J.;Lee, J.J.;Moon, Y.H.
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.50_51
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    • 2009
  • This paper describes the novel real-time embeded Dynamic System Monitor(KDSM) for dynamic device modeling and disturbace monitoring. The KDSM uses the variable resampling technique together with DFT algorithm so that it overcomes the shortcomings of the existing DFT algorithm at the big deviation of network frequency. The suggested algorithm is implemented by using the NI-PXI system, and verified by applying to the generator testing.

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A Simple Bias-Correction Rule for the Apparent Prediction Error

  • Beong-Soo So
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.146-154
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    • 1995
  • By using simple Taylor expansion, we derive an easy bias-correction rule for the apparent prodiction error of the predictor defined by the general M-estimators with respect to an arbitrary measure of prediction error. Our method has a considerable computational advantage over the previous methods based on the resampling thchnique such as Cross-validaton and Boothtrap. Connections with AIC, Cross-Validation and Boothtrap are discussed too.

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A New Method of Simulation Output Analysis : Threshold Bootstrap

  • Kim, Yun-Bae-
    • Proceedings of the Korea Society for Simulation Conference
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    • 1993.10a
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    • pp.2-2
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    • 1993
  • Inference for discrete event simulations usually relies on either independent replications or, if each simulation run is expensive, the method of batch means applied to a single replications. We present a new method, threshold bootstrap, which equals or exceeds the performance of independent replications or batch means. The method works by resampling runs of data created when a stationary time series crosses a threshold level, such as the sample mean of series. Computational results show that the threshold bootstrap matches or exceeds the performance of these alternative methods in estimating the standard deviation of the sample mean and producing valid confidence intervals.

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Development of Web-based Quality & Reliability System for Bootstrap on the Internet Environment (인터넷 환경에서 붓스트랩 품질 및 신뢰성 시스템의 개발)

  • Choi Sung woon;Lim In sup
    • Journal of the Korea Safety Management & Science
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    • v.7 no.1
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    • pp.147-157
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    • 2005
  • Recently, growth of internet causes rapid changes in many areas of statistics such as statistical computation and analysis. Especially, bootstrap is the most interesting statistical methods applying computer resampling simulation. In this paper, we try to present how to use a method of bootstrap on the internet. We also develop to user a statistical system which is programed with ASP for user to handle easily in manufacturing system.

A Study on the Improvement of Autofocusing Using Image Resampling Method (영상 재표본화에 의한 Autofocusing 속도 향상에 관한 연구)

  • 조택동;강문영;이호영
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.1
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    • pp.37-43
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    • 2003
  • A faster autofocusing method is proposed. The searching speed of microscope camera is limited by the long focusing time due to too much sampled digital image data. The improvement of autofocusing speed based on the down sampling is discussed analytically and is proved by experiments. The anticipated aliasing is found negligible in shilling rate of focus measure.

A Study on Image Interpolation Using SOFM and LAM (SOFM과 LAM을 이용한 영상 보간에 관한 연구)

  • Chang, Dong-Eon;Chung, Tae-Sang
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.640-642
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    • 1998
  • When resampling an image to a new set of coordinates, there is often a noticeable loss in image quality. The interpolation kernel determines the quality of interpolation. In this paper, We think two interpolation methods: cubic-spline method, neural net method, at first study given interpolation method using spline and then present new interpolation methon using SOFM and LAM(neural net method), finally compare the performance of several interpolation methods including replication, bilinear, spline and new methods.

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