### Table 3: Principal Component Analysis (Component Matrix)

2004

Cited by 1

### Table 4. Extracted principal components for project E

"... In PAGE 5: ... We extracted the principal components for each of the five projects that account for a cumulative sample variance greater than 95%. Table4 gives an example: After extracting five principal components, we can account for 96% of the total variance in project E. Therefore, five principal components suffice.... ..."

### Table 6. Results from analysis of principal components.

1998

"... In PAGE 11: ...Table6 . We used a normal principal component analysis with a orthotran/varimax transformation.... ..."

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### Table 3 Principal component analysis results

"... In PAGE 4: ... Principal component analysis was carried out for training data set with 6AE parameter. The eigen values of principal components (PCs) and their percentage proportions of corresponding variation for training data set are listed in Table3 . The variation of AE data could be acounted for over than 96% with only first two PCs.... ..."

### Table 9: Percentages of Variability and eigenvalues of the principal components.

2005

"... In PAGE 10: ...able 8: Methods Performances using per-band threshold selection................................. 82 Table9 : Percentages of Variability and eigenvalues of the principal components.... In PAGE 82: ....4.3 CPCA with Global Threshold Selection Figure 62, presents the image principal components obtained by performing the analysis over the HYPERION data. Table9 shows the variances and the percentages of variability obtained from the conventional analysis of principal components. The components selected for change detection were the ones outside a 90% of the total variability.... ..."

### TABLE 2 Principal Components and Dimensions of Housing Submarkets

"... In PAGE 23: ... TABLE2 (continued) Principal Components and Dimensions of Housing Submarkets Component Variable Factor loadings 5: Physical characteristics Tile roof 0.95 Iron roof -0.... ..."

### Table 5. Principal Component Analysis results.

"... In PAGE 10: ... 7. The PCA output is shown in Table5 . The first principal component shows positive coefficients for all variables, and so is a trend for inverted spectrum, variable sources to have higher values of circular polarization.... ..."

### Table 1. Eigenvectors for principal components Principal Variance Variable Eigenvector

1996

"... In PAGE 12: ... GSP data was also drawn from BEA-REIS, though this data is available only for 1977-1990. Empirical Results Results of the principal component analysis are presented in Table1 . Recall the interpretation of the eigenvector.... ..."

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### Table 2. Principal components loading of geometric variables

2003

"... In PAGE 14: ...Cs. That means 96.1% of the total variance in all the twelve geometric variables can be condensed into six PCs. Principal components loading (eigen vectors) of geometric variables are shown in Table2 . The loading plot (plot of eigen vectors), shown in Figure 4, can be used for further interpretation of results.... In PAGE 15: ...Figure 4. Loading plot of geometric variables The most important variables for the first PC were fat 11, fat 11 average, fat 11 minimum and fat 11 maximum ( Table2 ). These variables are related to subcutaneous fat thickness at 11 cm (from the mid line of the carcass).... ..."

### Table 5. Principal Component Analysis PC Singular

"... In PAGE 6: ... This regularization parameter reduces the condition number from 130 to 120. Table5 lists the local ridge parameters obtained through the evolutionary algorithm optimization and their corresponding filter factors. We see that the 2nd component (Year) is properly damped out, and that the last component is partially damped.... ..."