• 제목/요약/키워드: univariate analysis

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Development of a Method for Detecting Unstable Behaviors in Flume Tests using a Univariate Statistical Approach

  • Kim, Seul-Bi;Seo, Yong-Seok;Kim, Hyeong-Sin;Chae, Byung-Gon;Choi, Jung-Hae;Kim, Ji-Soo
    • 지질공학
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    • 제24권2호
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    • pp.191-199
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    • 2014
  • We describe a method for detecting slope instability in flume tests using pore pressure and water content data in conjunction with a statistical control chart analysis. Specifically, we conducted univariate statistical analysis on x-MR control chart data (pore pressure and water content) collected at several points along the flume slope, which we separated into three parts: upper, middle, and lower. To assess our results in the context of landslide forecasting and warning systems, we applied control limit lines at $1{\sigma}$, $2{\sigma}$, and $3{\sigma}$ levels of uncertainty. In doing so, we observed that dispersion time varies depending on the control limit line used. Moreover, the detection of instabilities is highly dependent on the position and type of sensor. Our findings indicate that different characteristics of the data on various factors predict slope failure differently and these characteristics can be identified by univariate statistical analysis. Therefore, we suggest that a univariate statistical approach is an effective method for the early detection of slope instability.

중량 앵커리지 블록과 연결된 조립 스테이 케이블의 장력 추정 (Estimation of Tension Forces of Assembly Stay Cables Connected with Massive Anchorage Block)

  • 정운;김남식
    • 한국소음진동공학회논문집
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    • 제15권3호
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    • pp.346-353
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    • 2005
  • In this paper, the tension of assembly stay cable connected with massive anchorage block was calculated through back analysis of in-situ frequencies measured from a stadium structure. Direct approach to back analysis is adopted using the univariate method among the direct search methods as an optimization technique. The univariate method can search the optimal tension without regard to the initial ones and has a rapid convergence rate. To verify the reliability of back analysis, Tension formulas proposed by Zui et al. and Shimada were used. Tensions estimated by three methods are compared with the design tension, and are in a reasonable agreement with an error of more or less than 15%. Therefore, it is shown that back analysis applied in this paper is appropriate for estimation of cable tension force.

중량 앵커리지 블록과 연결된 조립 스테이 케이블의 장력 추정 (Estimation of Tension Forces of Assembly Stay Cables Connected with Massive Anchorage Block)

  • 정운;김남식
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 추계학술대회논문집
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    • pp.435-440
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    • 2004
  • In this paper, the tension of assembly stay cable connected with massive anchorage block was calculated through back analysis of in-situ frequencies measured from a stadium structure. Direct approach to back analysis is adopted using the univariate method among the direct search methods as an optimization technique. The univariate method can search the optimal tension without regard to the initial ones and has a rapid convergence rate. To verify the reliability of back analysis, Tension formulas proposed by Zui et al. and Shimada were used. Tensions estimated by three methods are compared with the design tension, and are in a reasonable agreement with an error of more or less than 15%. Therefore, it is shown that back analysis applied in this paper is appropriate for estimation of cable tension force.

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Matrix Formation in Univariate and Multivariate General Linear Models

  • Arwa A. Alkhalaf
    • International Journal of Computer Science & Network Security
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    • 제24권4호
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    • pp.44-50
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    • 2024
  • This paper offers an overview of matrix formation and calculation techniques within the framework of General Linear Models (GLMs). It takes a sequential approach, beginning with a detailed exploration of matrix formation and calculation methods in regression analysis and univariate analysis of variance (ANOVA). Subsequently, it extends the discussion to cover multivariate analysis of variance (MANOVA). The primary objective of this study was to provide a clear and accessible explanation of the underlying matrices that play a crucial role in GLMs. Through linking, essentially different statistical methods, by fundamental principles and algebraic foundations that underpin the GLM estimation. Insights presented here aim to assist researchers, statisticians, and data analysts in enhancing their understanding of GLMs and their practical implementation in diverse research domains. This paper contributes to a better comprehension of the matrix-based techniques that can be extended to GLMs.

월유량에 대한 일변량 및 다변량 AR모형의 비교 (A Comparison of Univariate and Multivariate AR Models for Monthly River Flow Series)

  • 이원환;심재현
    • 물과 미래
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    • 제23권1호
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    • pp.99-107
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    • 1990
  • 수자원 개발계획 및 목공구조물의 합리적 설계를 위해서는 과거의 수문관측자료에 의거한 해석이 필요하며, 일반적인 수문현상은 무작위적인 인자가 포함되기 때문에 이를 고려한 통계적 기법, 즉 추계학적 해석기법이 필요하다고 하겠다. 본 연구에서는 남한강 상류의 동일유역 4개 지점(단양, 정선, 영월, 평창)의 월유량 자료를 일변량 AR(1), AR(2)모형과 다변량 AR(1), AR(2)모형에 적용하여 각 모형의 통계적 특성치를 분석하고, 월유량을 모의발생시켜, 일변량 모형과 다변량 모형을 비교하였다. 각각의 모형에 의한 모의발생 계열의 비교, 분석을 통하여 볼 때, 단일지점만을 고려하는 일변량 모형에 비해 지점간의 공선형성을 고려하는 다변량 모형이 동일유역의 월유량 해석에 있어서 더 적합함을 알 수 있었다.

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Decomposable polynomial response surface method and its adaptive order revision around most probable point

  • Zhang, Wentong;Xiao, Yiqing
    • Structural Engineering and Mechanics
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    • 제76권6호
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    • pp.675-685
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    • 2020
  • As the classical response surface method (RSM), the polynomial RSM is so easy-to-apply that it is widely used in reliability analysis. However, the trade-off of accuracy and efficiency is still a challenge and the "curse of dimension" usually confines RSM to low dimension systems. In this paper, based on the univariate decomposition, the polynomial RSM is executed in a new mode, called as DPRSM. The general form of DPRSM is given and its implementation is designed referring to the classical RSM firstly. Then, in order to balance the accuracy and efficiency of DPRSM, its adaptive order revision around the most probable point (MPP) is proposed by introducing the univariate polynomial order analysis, noted as RDPRSM, which can analyze the exact nonlinearity of the limit state surface in the region around MPP. For testing the proposed techniques, several numerical examples are studied in detail, and the results indicate that DPRSM with low order can obtain similar results to the classical RSM, DPRSM with high order can obtain more precision with a large efficiency loss; RDPRSM can perform a good balance between accuracy and efficiency and preserve the good robustness property meanwhile, especially for those problems with high nonlinearity and complex problems; the proposed methods can also give a good performance in the high-dimensional cases.

A Comparison Study of Multivariate Binary and Continuous Outcomes

  • Pak, Dae-Woo;Cho, Hyung-Jun
    • 응용통계연구
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    • 제25권4호
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    • pp.605-612
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    • 2012
  • Multivariate data are often generated with multiple outcomes in various fields. Multiple outcomes could be mixed as continuous and discrete. Because of their complexity, the data are often dealt with by separately applying regression analysis to each outcome even though they are associated the each other. This univariate approach results in the low efficiency of estimates for parameters. We study the efficiency gains of the multivariate approaches relative to the univariate approach with the mixed data that include continuous and binary outcomes. All approaches yield consistent estimates for parameters with complete data. By jointly estimating parameters using multivariate methods, it is generally possible to obtain more accurate estimates for parameters than by a univariate approach. The association between continuous and binary outcomes creates a gap in efficiency between multivariate and univariate approaches. We provide a guidance to analyze the mixed data.

Multivariate Analysis of the Prognosis of 37 Chondrosarcoma Patients

  • Yang, Zheng-Ming;Tao, Hui-Min;Ye, Zhao-Ming;Li, Wei-Xu;Lin, Nong;Yang, Di-Sheng
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권4호
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    • pp.1171-1176
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    • 2012
  • Objective: The current study aimedto screen for possible factors which affect prognosis of chondrosarcoma. Methods: Thirty seven cases were selected and analyzed statistically. The patients received surgical treatment at our hospital between December 2005 and March 2008. All of them had complete follow-up data. The survival rates were calculated by univariate analysis using the Kaplan-Meier method and tested by Log-rank. ${\chi}^2$ or Fisher exact tests were carried out for the numeration data. The significant indexes after univariate analysis were then analyzed by multivariate analysis using COX regression model. Based on the literature, factors of gender, age, disease course, tumor location, Enneking grades, surgical approaches, distant metastasis and local recurrence were examined. Results: Univariate analysis showed that there were significant differences in Enneking grades, surgical approaches and distant metastasis related to the patients' 3-year survival rate after surgery (P<0.001). No significant difference was not found in gender, age, disease course, tumor location or local recurrence (P>0.05). Multivariate analysis showed that Enneking grade (P=0.007) and surgical approaches (P=0.010) were independent factors affecting the prognosis of chondrosarcoma, but distant metastasis was not (P=0.942). Conclusion: Enneking grades, surgical approaches and distant metastasis are risk factors for prognosis of chondrosarcoma, among which the former two are independent factors.

일변량 자료의 왜도와 첨도에서 특이점의 영향을 평가하기 위한 탐색적 자료분석 그림도구로서의 불꽃그림 (Firework plot as a graphical exploratory data analysis tool for evaluating the impact of outliers in skewness and kurtosis of univariate data)

  • 문승호
    • 응용통계연구
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    • 제29권2호
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    • pp.355-368
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    • 2016
  • 특이점 및 영향점은 자료분석을 하는 데 사용되는 계량적이고 기술적인 많은 측도들을 왜곡한다. 각종 자료분석에 있어서의 특이점 검색을 위한 검정 통계량이나 그림도구에 관한 연구는 꾸준히 전개되어 왔다. Jang과 Anderson-Cook (2014)은 불꽃그림이란 이름을 붙인 그림도구를 발표하였는데 이상점이나 영향점이 일변량/이변량 자료분석 및 회귀분석에 어떠한 영향을 미치는지 알기 위하여 3-D 불꽃그림 및 불꽃그림 행렬을 제시하였다. 본 연구에서는 이러한 불꽃그림이 일변량 자료의 왜도와 첨도에서 특이점의 영향을 평가하기 위한 탐색적 자료분석 그림도구로서 사용될 수 있음을 보였다.

단변량 분석과 LVF 알고리즘을 결합한 하이브리드 속성선정 방법 (A Hybrid Feature Selection Method using Univariate Analysis and LVF Algorithm)

  • 이재식;정미경
    • 지능정보연구
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    • 제14권4호
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    • pp.179-200
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    • 2008
  • 본 연구에서는 사례기반 추론 기법을 대상으로 효율성과 효과성을 함께 증진시킬 수 있는 속성선정 방법을 개발하였다. 기본적으로, 본 연구에서 개발한 속성선정 방법은 기존에 개발된 단변량 분석 방법과 LVF 알고리즘을 통합하는 것이다. 먼저, 단변량 분석 방법 중 선택효과를 사용하여 전체 속성 중에서 예측력이 우수하다고 판단되는 일부분의 속성들을 추려낸다. 이 속성들로부터 생성해낼 수 있는 모든 가능한 부분집합을 생성해낸 후에, LVF 알고리즘을 이용하여 이 부분집합들이 가지는 불일치 비율을 평가함으로써 최종적으로 속성 부분집합을 선정한다. 본 연구에서 개발한 속성선정 방법을 UCI에서 제공하는 데이터 집합들에 적용하여 성능을 측정한 후, 기존 기법의 성능들과 비교한 결과, 본 연구에서 개발된 속성선정 방법이 선정된 속성의 개수도 만족할만하고 적중률도 향상되어서, 효율성과 효과성 모두의 측면에서 우수함을 보였다.

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