• Proceedings of the Korean Statistical Society Conference
• /
• 2003.05a
• /
• pp.163-165
• /
• 2003

Some multivariate analyses provide configurations for variables or objects in low dimensional space because we can see easily their relation. In particular, in simple correspondence analysis(SCA), we can obtain the various configurations which are called SCA Maps based on the algebraic algorithms. Moreover, it often occur the variability among them. Therefore, in this study, we will give a comparison of variability of SCA maps using the procrustes analysis which is a technique of comparing configurations in multidimensional scaling.

• Journal of Korean Institute of Industrial Engineers
• /
• v.20 no.4
• /
• pp.73-84
• /
• 1994

Output analysis is one of the most important fields of simulation to achieve the accurate simulation results. This study shows how to analyze simulation output data in the steady state using Procrustes analysis technique which has not been used in the field of simulation yet. In this paper Procrustes analysis method is used to perform the analysis of simulation output efficiently and effectively by applying the improved version of the method. The experiments are conducted using M/M/1 queueing simulation model. The results obtained by Procrustes analysis method show better estimates for average waiting times and average queue lengths which are closer to true values and narrower confidence intervals than when replication-deletion method is used. Also it requires the smaller number of simulation runs.

• The Korean Journal of Applied Statistics
• /
• v.22 no.4
• /
• pp.855-864
• /
• 2009

Canonical correlation biplot is 2-dimensional plot for investigating the relationship between two sets of variables and the relationship between observations and variables in canonical correlation analysis graphically. Recently, Choi and Choi (2008) suggested a method for investigating the relationship between skill and competition score factors of KLPGA players using canonical correlation biplot and cluster analysis. analysis. Procrustes analysis is very useful tool for comparing shape between configurations. Therefore, in this study, we will provide a method for investigating the relationship between player characteristic factors and competitive factors of tennis grand slams competition using Canonical correlation biplot and Procrustes analysis.

• Communications for Statistical Applications and Methods
• /
• v.25 no.6
• /
• pp.673-685
• /
• 2018

Procrustes analysis is a useful technique useful to measure, compare shape differences and estimate a mean shape for objects; however it is based on a least squares criterion and is affected by some outliers. Therefore, we propose two generalized Procrustes analysis methods based on M-estimation and least median of squares estimation that are resistant to object outliers. In addition, two algorithms are given for practical implementation. A simulation study and some examples are used to examine and compared the performances of the algorithms with the least square method. Moreover since these resistant GPA methods are available for higher dimensions, we need some methods to visualize the objects and mean shape effectively. Also since we have concentrated on resistant fitting methods without considering shape distributions, we wish to shape analysis not be sensitive to particular model.

• Communications for Statistical Applications and Methods
• /
• v.17 no.6
• /
• pp.917-925
• /
• 2010

The canonical correlation biplot is a 2-dimensional plot for graphically investigating the relationship between two sets of variables and the relationship between observations and variables in the canonical correlation analysis. Recently, Choi and Choi (2008) suggested a method for investigating the relationship between skill and competition score factors of KLPGA players using this biplot. Choi et al. (2010) used this biplot to analyze the player characteristic factors and competitive factors of tennis Grand Slam competition. Moreover, Huh (1999) provided a generalized canonical correlation analysis and biplot for more than three sets of variables. A Procrustes analysis is a useful tool for comparing shapes between configurations. This study will provide a method to investigate the relationship between physique, physical fitness and basic skill factors of tennis players in the Korea Tennis Association using a generalized canonical correlation biplot and Procrustes analysis.

• Communications for Statistical Applications and Methods
• /
• v.30 no.1
• /
• pp.37-48
• /
• 2023

Shape analysis is a method for measuring, describing and comparing the shape of objects in geometric space. An important aspect is to obtain Procrustes distance based on least square method. We note that the shape is all the geometrical information that remains when location, scale and rotational effects are filtered out from an object. However, and unfortunately, when we cannot measure some landmarks which are some biologically or geometrically meaningful points of any object, it is not possible to measure the variation of all shapes of an object, including that of the incomplete object. Hence, we need to replace the missing landmarks. In particular, Albers and Gower (2010) studied the missing rows of configurations in Procrustes analysis. They noted that the convergence of their approach can be quite slow. In this study, alternatively, we derive an algorithm for estimating the missing landmarks based on the pre-shapes. The pre-shape is invariant under the location and scaling of the original configuration with the centroid size of the pre-shape being one. Therefore we expect that we can reduce the amount of total computing time for obtaining the estimate of the missing landmarks.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2006.05a
• /
• pp.710-714
• /
• 2006

지역빈도해석기법은 수문학적으로 성질이 유사한 지점을 하나의 군으로 구성한 자료를 이용해서 빈도해석을 하는 기법으로, 지점빈도해석이 가질 수 있는 단점들을 보완하기 위한 방안의 하나로 기대되고 있다. 본 논문은, 지역빈도해석기법을 적용하기 위한 단계중의 하나인 군집해석에 사용되는 변수들을 보다 효율적으로 선택하기 위한 연구로서, 다변량 분석방법인 주성분분석과 요인분석, 그리고, 변수선택을 위한 Procrustes Analysis를 통해서 보다 효율적으로 변수를 선택하는 방법을 제안하기 위한 연구이다.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1993.10a
• /
• pp.1-1
• /
• 1993

시뮬레이션 분야에서 출력 분석은 중요한 분야중의 하나로 출력 분석을 정확히 하기 위해서, 지금까지 많은 연구가 진행되어 왔다. 본 연구에서는 현재까지 시뮬레이션 출력 분석 분야에서 사용되지 않았던 프로크루스테스 분석(Procrustes Analysis) 방법을 사용하여 시뮬레이션 출력 데이타의 안정상태(steady state)를 분석하는 방법을 제시한다. 본 논문에서 사용하는 프로크루스테스 분석 방법은 시뮬레이견 출력 분석을 효과적으로 수행할 수 있도록 앨고리듬을 개선하여 적용하며, M/M/1 대기모형을 대상으로 시뮬레이션을 수행한다. M/M/1 대기모형에서 대기열의 평균대기시간과 평균길이라는 두가지 매개변수에 대한 출력 데이타를 동시에 사용하여, 프로크루스테스 분석을 행한 결과와 시뮬레이션 출력 분석에서 일반적으로 쓰이는 반복-제거 방법(replication-deletion approach)을 비교한 결과, 시뮬레이션 실행 횟수를 줄여도 추정하고자 하는 참값에 보다 더 가깝고 신뢰 구간의 폭이 더 좁은 추정치를 얻는다.

• Journal of Korea Water Resources Association
• /
• v.41 no.5
• /
• pp.517-525
• /
• 2008

Regional rainfall quantile depends on the identification of hydrologically homogeneous regions. Various variables relevant to precipitation can be used to form regions. Since the type and number of variables may lead to improve the efficiency of partitioning, it is important to select those precipitation related variables, which represent most of the information from all candidate variables. Multivariate analysis techniques can be used for this purpose. Procrustes analysis which can decrease the dimension of variables based on their correlations, are applied in this study. 42 rainfall related variables are decreased into 21 ones by Procrustes analysis. Factor analysis is applied to those selected variables and then 5 factors are extracted. Fuzzy-c means technique classifies 68 stations into 6 regions. As a result, the GEV distributions are fitted to 6 regions while the lognormal and generalized logistic distributions are fitted to 5 regions. For the comparison purpose with previous results, rainfall quantiles based on generalized logistic distribution are estimated by at-site frequency analysis, index flood method, and regional shape estimation method.

• Communications for Statistical Applications and Methods
• /
• v.19 no.1
• /
• pp.97-105
• /
• 2012

The generalized canonical correlation biplot is a 2-dimensional plot to graphically investigate the relationship between more than three sets of variables and the relationship between observations and variables. Recently, Choi and Choi (2010) investigated the relationship physique, physical fitness and basic skill factors of Korea Tennis Association(KTA) players of using this biplot; however we consider the set of covariate variables affecting the linearly on two sets of variables. In this case, if we apply the generalized canonical correlation biplot, we cannot clearly interpret the other two sets of variables due to the effect of the set of covariate variables. Moreover, Yeom and Choi (2011) provided partial canonical correlation analysis that removed the linear effect of the set of covariate variables on two sets of variables. In addition, Procrustes analysis is a useful tool for comparing shape between configurations. In this study, we will investigate the relationship between physical fitness and basic skill factors of KTA players of using a partial canonical correlation biplot and Procrustes analysis. We compare shapes and shape variabilities for the generalized, partial and simple canonical correlation biplots.