• 제목/요약/키워드: Multivariate statistical method

검색결과 295건 처리시간 0.02초

배열을 이용한 효과적인 일부실시법의 설계 및 분석방법에 관한 연구 (A Study on the Construction and Analysis of Fractional Designs by Using Arrays for Factorial Experiments)

  • 김상익
    • 품질경영학회지
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    • 제40권1호
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    • pp.15-24
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    • 2012
  • For the construction of fractional factorial designs, the various arrays can be widely used. In this paper we review the statistical properties of fractional designs constructed by two arrays such as orthogonal array and partially balanced array, and develop a quick and easy method for analyzing unreplicated saturated designs. The proposed method can be characterized that we control the error rate by experiment-wise way and exploit the multivariate Student $t$-distribution. Especially the proposed method can be used efficiently together with some exploratory analysis methods, such as half normal probability plot method.

A Automatic Document Summarization Method based on Principal Component Analysis

  • Kim, Min-Soo;Lee, Chang-Beom;Baek, Jang-Sun;Lee, Guee-Sang;Park, Hyuk-Ro
    • Communications for Statistical Applications and Methods
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    • 제9권2호
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    • pp.491-503
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    • 2002
  • In this paper, we propose a automatic document summarization method based on Principal Component Analysis(PCA) which is one of the multivariate statistical methods. After extracting thematic words using PCA, we select the statements containing the respective extracted thematic words, and make the document summary with them. Experimental results using newspaper articles show that the proposed method is superior to the method using either word frequency or information retrieval thesaurus.

주성분을 이용한 다변량 고빈도 실현 변동성의 주기 선택 (Choice of frequency via principal component in high-frequency multivariate volatility models)

  • 진민경;윤재은;황선영
    • 응용통계연구
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    • 제30권5호
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    • pp.747-757
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    • 2017
  • 본 논문은 다변량 실현 변동성 계산에서 주기 선택 방안에 대해 연구하고 있다. 고빈도(high frequency) 시계열 자료에 기초한 일간 변동성인 실현변동성을 계산하고 차원 축소 방법인 주성분을 도입하였다. Cholesky 모형을 포함한 다양한 다변량 변동성모형을 주성분을 통해 비교하였으며 KOSPI/삼성전자/현대차 고빈도 수익률 자료를 이용하여 예시하였다.

Constructing Simultaneous Confidence Intervals for the Difference of Proportions from Multivariate Binomial Distributions

  • Jeong, Hyeong-Chul;Kim, Dae-Hak
    • 응용통계연구
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    • 제22권1호
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    • pp.129-140
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    • 2009
  • In this paper, we consider simultaneous confidence intervals for the difference of proportions between two groups taken from multivariate binomial distributions in a nonparametric way. We briefly discuss the construction of simultaneous confidence intervals using the method of adjusting the p-values in multiple tests. The features of bootstrap simultaneous confidence intervals using non-pooled samples are presented. We also compute confidence intervals from the adjusted p-values of multiple tests in the Westfall (1985) style based on a pooled sample. The average coverage probabilities of the bootstrap simultaneous confidence intervals are compared with those of the Bonferroni simultaneous confidence intervals and the Sidak simultaneous confidence intervals. Finally, we give an example that shows how the proposed bootstrap simultaneous confidence intervals can be utilized through data analysis.

표준 측정치의 오차를 고려한 다변량 계기 교정 절차 (A Multivariate Calibration Procedure When the Standard Measurement is Also Subject to Error)

  • 이승훈
    • 대한산업공학회지
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    • 제19권2호
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    • pp.35-41
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    • 1993
  • Statistical calibration is a useful technique for achieving compatibility between two different measurement methods, and it usually consists of two steps : (1) estimation of the relationship between the standard and nonstandard measurements, and (2) prediction of future standard measurements using the estimated relationship and observed nonstandard measurements. A predictive multivariate errors-in-variables model is presented for the multivariate calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the maximum likelihood (ML) estimation method is considered. It is shown that the direct and the inverse predictors for the future unknown standard measurement are the same under ML estimation. Based upon large-sample approximations, the mean square error of the predictor is derived.

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다변량 정규성검정을 위한 근사 SHAPIRO-WILK 통계량의 일반화 (An Approximate Shapiro -Wilk Statistic for Testing Multivariate Normality)

  • 김남현
    • 응용통계연구
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    • 제17권1호
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    • pp.35-47
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    • 2004
  • 본 논문에서는 Kim & Bickel(2003)에서 제안한 이변량 정규분포를 위한 검정통계량을 Fattorini(1986)의 방법을 이용하여 이변량 이상인 경우에도 실제적으로 사용가능 하도록 일반화하였다. Fattorini(1986)의 통계량은 Shapiro & Wilk(1965)의 일변량 정규분포를 위한 검정통계량을 다변량으로 확장한 것이다. 그리고 제안된 통계량은 Fat-torini(1986) 통계량의 근사통계량으로 생각할 수 있으며 표본의 크기가 클 때도 사용 가능하다. 또한 모의실험을 통하여 여러 가지 대립가설에서 기존의 통계량과의 검정력을 비교하였다.

Comparison of Parameter Estimation Methods in the Analysis of Multivariate Categorical Data with Logit Models

  • Song, Hae-Hiang
    • Journal of the Korean Statistical Society
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    • 제12권1호
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    • pp.24-35
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    • 1983
  • In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

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Robust Inference for Testing Order-Restricted Inference

  • Kang, Moon-Su
    • 응용통계연구
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    • 제22권5호
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    • pp.1097-1102
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    • 2009
  • Classification of subjects with unknown distribution in small sample size setup may involve order-restricted constraints in multivariate parameter setups. Those problems makes optimality of conventional likelihood ratio based statistical inferences not feasible. Fortunately, Roy (1953) introduced union-intersection principle(UIP) which provides an alternative avenue. Redescending M-estimator along with that principle yields a considerably appropriate robust testing procedure. Furthermore, conditionally distribution-free test based upon exact permutation theory is used to generate p-values, even in small sample. Applications of this method are illustrated in simulated data and read data example (Lobenhofer et al., 2002)

Bootstrap Confidence Intervals of Classification Error Rate for a Block of Missing Observations

  • Chung, Hie-Choon
    • Communications for Statistical Applications and Methods
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    • 제16권4호
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    • pp.675-686
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    • 2009
  • In this paper, it will be assumed that there are two distinct populations which are multivariate normal with equal covariance matrix. We also assume that the two populations are equally likely and the costs of misclassification are equal. The classification rule depends on the situation when the training samples include missing values or not. We consider the bootstrap confidence intervals for classification error rate when a block of observation is missing.