• Title/Summary/Keyword: Two-dimensional plot

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A Predictive Study on Molecular and Explosive Properties of 1-Aminoimidazole Derivatives

  • Cho, Soo-Gyeong
    • Bulletin of the Korean Chemical Society
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    • v.32 no.7
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    • pp.2319-2324
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    • 2011
  • Molecular structures and chemical properties of 1-aminoimidazole derivatives have been investigated at high levels of density functional theories. Heat of formation, density, explosive performances and impact sensitivities have been estimated at the global minimum of potential energy surface. As more nitro groups are introduced, the explosive performances of 1-aminoimidazole derivatives are enhanced, while the impact sensitivity becomes more sensitive. A two-dimensional plot between explosive performance and impact sensitivity has been utilized to comprehend the technical status of new explosive candidates. Based on locations in the two-dimensional plot, 1-aminodinitroimidzole isomers appears to have a potential to be good candidates for insensitive explosives, and 1-aminotrinitroimidazole may become a powerful explosive molecule whose behavior is quite close to HMX.

Graphical method for evaluating the impact of influential observations in high-dimensional data (고차원 자료에서 영향점의 영향을 평가하기 위한 그래픽 방법)

  • Ahn, Sojin;Lee, Jae Eun;Jang, Dae-Heung
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.6
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    • pp.1291-1300
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    • 2017
  • In the high-dimensional data, the number of variables is very larger than the number of observations. In this case, the impact of influential observations on regression coefficient estimates can be very large. Jang and Anderson-Cook (2017) suggested the LASSO influence plot. In this paper, we propose the LASSO influence plot, LASSO variable selection ranking plot, and three-dimensional LASSO influence plot as graphical methods for evaluating the impact of influential observations in high-dimensional data. With real two high-dimensional data examples, we apply these graphical methods as the regression diagnostics tools for finding influential observations. It has been found that we can obtain influential observations with by these graphical methods.

Contour Method and Collapsibility Criteria for $2{\times}3{\times}K$ Contingency Tables

  • Hong, C.S.;Son, B.U.;Park, J.Y.
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.4
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    • pp.717-729
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    • 2004
  • The contour method which was originally designed for $2{\times}2{\times}2$ contingency table is studied for $2{\times}2{\times}K$ and $2{\times}3{\times}K$ tables. Whereas a contour plot for a $2{\times}2{\times}K$ table is represented on unit squared two dimensional plane, a contour plot of a $2{\times}3{\times}K$ table can be expressed with a regular hexahedron on three dimensional space. Based on contour plots for categorical data fitted to all possible three dimensional log-linear models, one might identify whether $2{\times}2{\times}k$ or $2{\times}3{\times}K$ tables are collapsible over the third variable.

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Correlation plot for a contingency table

  • Hong, Chong Sun;Oh, Tae Gyu
    • Communications for Statistical Applications and Methods
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    • v.28 no.3
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    • pp.295-305
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    • 2021
  • Most graphical representation methods for two-dimensional contingency tables are based on the frequencies, probabilities, association measures, and goodness-of-fit statistics. In this work, a method is proposed to represent the correlation coefficients for each of the two selected levels of the row and column variables. Using the correlation coefficients, one can obtain the vector-matrix that represents the angle corresponding to each cell. Thus, these vectors are represented as a unit circle with angles. This is called a CC plot, which is a correlation plot for a contingency table. When the CC plot is used with other graphical methods as well as statistical models, more advanced analyses including the relationship among the cells of the row or column variables could be derived.

TPR-TNR plot for confusion matrix

  • Hong, Chong Sun;Oh, Tae Gyu
    • Communications for Statistical Applications and Methods
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    • v.28 no.2
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    • pp.161-169
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    • 2021
  • The two-dimensional confusion matrix used in credit assessment, biostatistics, and many other fields consists of true positive, true negative, false positive, and false negative. Their rates, such as the true positive rate (TPR), true negative rate (TNR), false positive rate, and false negative rate, can be applied to measure its accuracy. In this study, we propose the TPR-TNR plot, a graphical method that can geometrically describe and explain these rates based on the confusion matrix. The proposed TPR-TNR plot consists of two right-angled triangles. We obtain that the TPR and TNR describe the acute angles of right-angled triangles in the plot. These acute angles can be used to determine optimal thresholds corresponding to lots of accuracy measures.

Three Dimensional Dynamic Added Variable Plots

  • Seo, Han-Son
    • Communications for Statistical Applications and Methods
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    • v.11 no.2
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    • pp.345-353
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    • 2004
  • Graphical methods for the specification of the curvature as a function of two predictors are animated to see the effect of an added variable to the model. Through a 3D animated plot it might be difficult to find a sequence of interpretable plots. But examples demonstrate that useful information can be obtained by using rotation technique in 3D plot. Besides 3D plots, an example of 2D animated plot applied to the case of high correlation between predictors and an added predictor is also given. It implies that speed of the convergence to a certain image in a dynamic plot may be understood as an influence of collinearity.

Applications of Parallel Coordinate Plots for Visualizing Gene Expression Data (평행좌표 플롯을 활용한 유전자발현 자료의 시각화)

  • Park, Mi-Ra;Kwak, Il-Youp;Huh, Myung-Hoe
    • The Korean Journal of Applied Statistics
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    • v.21 no.6
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    • pp.911-921
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    • 2008
  • Visualization of the gene expression data on a low-dimensional graph is helpful in uncovering biological information contained in the data. In this study, we focus on two modified versions of the parallel coordinate plot. First one is the ePCP(enhanced parallel coordinate plot) which shows "near smooth" connecting curves between axes spaced proportionately to the proximity of re-ordered variables. Second one is APCP(Andrews' type parallel coordinate plot) which is obtained by rotating Andrews' plot that has a form of the parallel coordinate plot. Visualization procdures using ePCP and APCP are given for the lymphoma data case.

GIS Application for Site Planning

  • Han, Seung-Hee;Lee, Jin-Duk
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.1
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    • pp.53-59
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    • 2009
  • The general urban plan is the plane plan which limits general and uniformed constructions; however, the district unit plan is the solid plan that can leads various constructions by discriminating by plot, housing area and lot. Therefore, for the zone plan, not only the two-dimensional plot information such as plot usage plan, but also the three-dimensional plot information needs to be used to analyze lighting, sewerage and directions. To fulfill such requirements, the information can be gathered using GIS and photogrammetric method for the reasonable and efficient zone plan. In this research, the information about the testing area for the zone plan has been gathered using GIS method, and the three-dimensional model about the area has been built using the satellite image and DEM. As the result, plot usage analysis, direction analyst, water system analysis, and slope analysis has been done and used efficiently to build the district unit plan. Also, after the result after applying the analyzed result to the actual area says this is very appropriate and efficient.

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Evaluation of three-dimensional cole-cole parameters from spectral IP data

  • Yang Jeong-Seok;Kim Hee Joon
    • 한국지구물리탐사학회:학술대회논문집
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    • 2003.11a
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    • pp.383-389
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    • 2003
  • Clay minerals show a distinct induced-polarization phenomenon, which is one of the most important factors for predicting groundwater flow and contaminant transport. This paper presents a step-by-step process to estimate Cole-Cole parameters from spectral induced-polarization (IP) data measured on the surface of three-dimensional earth. First, the inversion of low-frequency resistivity survey data is made to identify the dc resistivity ${\rho}_dc$ of a volume having IP effects. The other parameters, chargeability m, time constant $\tau$, and frequency dependence c, are sought for the polarizable volume. Next, using multi-frequency data, c can be obtained as high or low asymptotes of the slope of log phase vs. log frequency. Further, for low m, intrinsic $\tau$ is approximated by apparent one, ${\tau}_a$, which is derived from the relation ${{\omega}{\tau}}_a$=1 at an angular frequency $\omega$, where the imaginary component of spectral IP data has an extreme value. Finally, to obtain intrinsic m a two-step linearized procedure has been derived. For a body of given $\tau$ and c, forward modeling with a progression of m values yields a plot of observed vs. intrinsic imaginary components for a frequency. Since this plot is essentially linear, to extract the intrinsic imaginary component is quite simple with an observed value. Using the plot of intrinsic imaginary component vs. m, intrinsic m is determined. We present a synthetic example to illustrate that the Cole-Cole parameters can be recovered from spectral IP data.

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INFLUENCE FUNCTIONS IN MULTIPLE CORRESPONDENCE ANALYSIS (다중 대응 분석에서의 영향 함수)

  • Hong Gie Kim
    • The Korean Journal of Applied Statistics
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    • v.7 no.1
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    • pp.69-74
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    • 1994
  • Kim (1992) derived influence functions of rows and columns on the eigenvalues obtained in correspondence analysis (CA) of two-way contingency tables. As in principal component analysis, the eigenvalues are of great importance in CA. The goodness of a two dimensional correspondence plot is determined by the ratio of the sum of the two largest eigenvalues to the sum of all the eigenvalues. By investigating those rows and columns with high influence, a correspondence plot may be improved. In this paper, we extend the influence functions of CA to multiple correspondence analysis (MCA), which is a CA of multi-way contigency tables. An explicit formula of the influence function is given.

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