• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.421-428
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• 2009

On the visualization of categorical data, if the number of categories is small, we can consider Hayashi Quantification Method 3 for visualization of the categories of the variables. But it is known that the method is unstable because it quantifies more significantly for the small frequency categories rather than large frequency categories. The purpose of this research is to propose the visualization of large two-way crosstabulation data by PLS methods for checking the relationship between the categories of row and column variables. In this research, we utilize the PLS visualization methods (Huh et al., 2007) that is proposed for visualization of the qualitative data to visualize the categories of the large categorical data. We also compared both methods by applying them to real data, and studied the results from PLS visualization method on the real categorized data with many categories.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.345-355
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• 2007

PLS methods are suited for regressing q-variate Y variables on p-variate X variables even in the presence of multicollinearity problem among X variables. Consequently, they are useful for analyzing datasets with smaller number of observations compared to the number of variables, such as NIR(near-infrared) spectroscopy data in chemometrics. In this study, we propose two visualizing methods of p-variate X variables and q-variate Y variable that can be used in connection with PLS analysis.