• 제목/요약/키워드: Residual variance

검색결과 145건 처리시간 0.025초

Bivariate EWMA Control Charts for Autocorrelated Processes

  • 조교영;안영선
    • Journal of the Korean Data and Information Science Society
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    • 제13권1호
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    • pp.105-112
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    • 2002
  • In this paper we establish bivariate exponentially weighted moving average (EWMA) control charts for autocorrelated processes using residual vectors. We first derive the residual vectors, their expectation, variance-covariance matrix, then evaluate the control chart based on the average run length (ARL).

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Multivariate CUSUM Charts with Correlated Observations

  • 조교영;안영선
    • Journal of the Korean Data and Information Science Society
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    • 제12권1호
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    • pp.127-133
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    • 2001
  • In this article we establish multivariate cumulative sum (CUSUM) control charts based on residual vector with correlated observations. We first find the residual vector and its expectation and variance-covariance matrix and then evaluate the average run length (ARL) of the control charts.

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로지스틱회귀에서 잔차산점도를 이용한 모형평가 (Model assessment with residual plot in logistic regression)

  • 강명욱
    • Journal of the Korean Data and Information Science Society
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    • 제26권1호
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    • pp.141-150
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    • 2015
  • 로지스틱회귀에서 모형을 평가하거나 진단할 때 가설검정이 주로 사용되지만 이것만으로는 놓칠 수 있는 부분이 많고 이에 대한 보완을 위하여 그래픽적 방법의 사용이 요구된다. 그래프를 이용한 모형의 적절성 평가를 위한 도구로 잔차산점도가 널리 이용되고 있으나 적용 범위가 선형회귀에 국한되는 문제점이 있다. 해결 방안으로 주변모형산점도를 이용하여 모형의 적절성을 평가하는 방법이 있으나 역시 문제점을 가지고 있다. 본 논문에서는 주변모형산점도의 대안으로 카이잔차산점도를 제안하고 그 효용성을 알아본다.

평활 적합도 검정에서의 분산추정의 영향 (A Study On Variance Estimation in Smoothing Goodness-of-Fit Tests)

  • 윤용화;김종태;이우동
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.189-202
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    • 1998
  • 본 연구는 Rice 분산추정량을 사용한 기존의 평활 적합도 검정들에 있어서 Rice의 분산 추정량 보다 뛰어난 성질을 가지는 GSJS 추정량을 사용함으로 검정 통계량들에 대한 검정력에 미치는 영향을 조사하는데 그 목적을 둔다. 또한 분산의 값들의 변화가 진동수와 진폭에 따른 선형 모형에서의 검정력들에 미치는 영향을 관찰하였다.

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불확정성을 고려한 적층판 결합공정의 강건최적설계 (A Study on Robust Design Optimization of Layered Plates Bonding Process Considering Uncertainties)

  • 이우혁;박정진;최주호;이수용
    • 대한기계학회논문집A
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    • 제31권1호
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    • pp.113-120
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    • 2007
  • Design optimization of layered plates bonding process is conducted by considering uncertainties in a manufacturing process, in order to reduce the crack failure arising due to the residual stress at the surface of the adherent which is caused by different thermal expansion coefficients. Robust optimization is peformed to minimize the mean as well as its variance of the residual stress, while constraining the distortion as well as the instantaneous maximum stress under the allowable reliability limits. In this optimization, the dimension reduction (DR) method is employed to quantify the reliability such as mean and variance of the layered plate bonding. It is expected that the DR method benefits the optimization from the perspectives of efficiency, accuracy, and simplicity. The obtained robust optimal solution is verified by the Monte Carlo simulation.

Length-biased Rayleigh distribution: reliability analysis, estimation of the parameter, and applications

  • Kayid, M.;Alshingiti, Arwa M.;Aldossary, H.
    • International Journal of Reliability and Applications
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    • 제14권1호
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    • pp.27-39
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    • 2013
  • In this article, a new model based on the Rayleigh distribution is introduced. This model is useful and practical in physics, reliability, and life testing. The statistical and reliability properties of this model are presented, including moments, the hazard rate, the reversed hazard rate, and mean residual life functions, among others. In addition, it is shown that the distributions of the new model are ordered regarding the strongest likelihood ratio ordering. Four estimating methods, namely, method of moment, maximum likelihood method, Bayes estimation, and uniformly minimum variance unbiased, are used to estimate the parameters of this model. Simulation is used to calculate the estimates and to study their properties. Finally, the appropriateness of this model for real data sets is shown by using the chi-square goodness of fit test and the Kolmogorov-Smirnov statistic.

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Data Visualization using Linear and Non-linear Dimensionality Reduction Methods

  • Kim, Junsuk;Youn, Joosang
    • 한국컴퓨터정보학회논문지
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    • 제23권12호
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    • pp.21-26
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    • 2018
  • As the large amount of data can be efficiently stored, the methods extracting meaningful features from big data has become important. Especially, the techniques of converting high- to low-dimensional data are crucial for the 'Data visualization'. In this study, principal component analysis (PCA; linear dimensionality reduction technique) and Isomap (non-linear dimensionality reduction technique) are introduced and applied to neural big data obtained by the functional magnetic resonance imaging (fMRI). First, we investigate how much the physical properties of stimuli are maintained after the dimensionality reduction processes. We moreover compared the amount of residual variance to quantitatively compare the amount of information that was not explained. As result, the dimensionality reduction using Isomap contains more information than the principal component analysis. Our results demonstrate that it is necessary to consider not only linear but also nonlinear characteristics in the big data analysis.

자기상관 공정 적용을 위한 잔차 기반 강건 누적합 관리도 (Residual-based Robust CUSUM Control Charts for Autocorrelated Processes)

  • 이현철
    • 산업경영시스템학회지
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    • 제35권3호
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    • pp.52-61
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    • 2012
  • The design method for cumulative sum (CUSUM) control charts, which can be robust to autoregressive moving average (ARMA) modeling errors, has not been frequently proposed so far. This is because the CUSUM statistic involves a maximum function, which is intractable in mathematical derivations, and thus any modification on the statistic can not be favorably made. We propose residual-based robust CUSUM control charts for monitoring autocorrelated processes. In order to incorporate the effects of ARMA modeling errors into the design method, we modify parameters (reference value and decision interval) of CUSUM control charts using the approximate expected variance of residuals generated in model uncertainty, rather than directly modify the form of the CUSUM statistic. The expected variance of residuals is derived using a second-order Taylor approximation and the general form is represented using the order of ARMA models with the sample size for ARMA modeling. Based on the Monte carlo simulation, we demonstrate that the proposed method can be effectively used for statistical process control (SPC) charts, which are robust to ARMA modeling errors.

한국연안 일평균 조위편차의 시공간적 변동 특성 (Characteristics of Spatio-temporal Variability of Daily averaged Tidal Residuals in Korean Coasts)

  • 김호균;김영택
    • 해양환경안전학회지
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    • 제19권6호
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    • pp.561-569
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    • 2013
  • 본 연구에서는 우리나라 연안의 2003~2009년 해수면자료로 조위편차를 산출하고, 일평균조위편차의 시공간적 변동을 EOF 분석, 해면기압과 바람이 조위편차 변동에 얼마나 영향을 미치는지를 상관성 분석을 통해 알아보았다. 일평균조위편차는 전체 변동량의 68 %(제1모드)가 동시승강하였고, 전체 변동량의 21 %(제2모드)는 서해안이 상승할 때 남해안과 동해안이 하강하는 교차승강을 하였다. 해역별로 조위편차에 영향을 주는 주요 요인을 보면, 서해안은 남-북 방향의 바람 성분이었고, 남해안은 동해안으로 갈수록 해면기압의 영향이 우세하였다.

Application of random regression models for genetic analysis of 305-d milk yield over different lactations of Iranian Holsteins

  • Torshizi, Mahdi Elahi;Farhangfar, Homayoun;Mashhadi, Mojtaba Hosseinpour
    • Asian-Australasian Journal of Animal Sciences
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    • 제30권10호
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    • pp.1382-1387
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    • 2017
  • Objective: During the last decade, genetic evaluation of dairy cows using longitudinal data (test day milk yield or 305-day milk yield) using random regression method has been officially adopted in several countries. The objectives of this study were to estimate covariance functions for genetic and permanent environmental effects and to obtain genetic parameters of 305-day milk yield over seven parities. Methods: Data including 60,279 total 305-day milk yield of 17,309 Iranian Holstein dairy cows in 7 parities calved between 20 to 140 months between 2004 and 2011. Residual variances were modeled by homogeneous and step functions with 7 and 10 classes. Results: The results showed that a third order polynomial for additive genetic and permanent environmental effects plus a step function with 10 classes for the residual variance was the most adequate and parsimonious model to describe the covariance structure of the data. Heritability estimates obtained by this model varied from 0.17 to 0.28. The performance of this model was better than repeatability model. Moreover, 10 classes of residual variance produce the more accurate result than 7 classes or homogeneous residual effect. Conclusion: A quadratic Legendre polynomial for additive genetic and permanent environmental effects with 10 step function residual classes are sufficient to produce a parsimonious model that explained the change in 305-day milk yield over consecutive parities of Iranian Holstein cows.