<p>The PCA analysis was used to determine if outlying points exhibited a different relationship with Euclidean distance than the majority of the points. Points that were in the upper or lower 5% in terms of displacement from the primary axis of variance are colored red and suggest that there is no systematic relationship between correlation differences and Euclidean distances for the outlying points. The red line represents the primary axis of variance.</p
<p>A. Correlation circle of the variables used for the PCA, projected on the first two components. B...
A to C show the results of the PCA based on the 2D plane corresponding to the first 2 axes. D to F s...
<p>A, B and C: Hyperplane between the first and second principal components (PC1 and PC2, respective...
<p>Ellipsoids represent the 95% confidence interval and are a measure for the distance of relationsh...
<p>Principal coordinate analyses (PCA) were performed according to A.) <i>F</i><sub>ST</sub>, B.) <i...
<p>Samples are projected onto the plane formed by the first two principal axes. The first factor exp...
Gower and Krzanowski (1999) described the analysis of a multivariate dataset that violated the assum...
<p>The variance explained by each principal coordinate axis is shown in parentheses. Datasets were s...
A) PCA carried out on full dataset. B) standard deviations of first 10 PCs indicate that the first P...
<p>Scatter plot of individuals, showing the first two principal components. Each symbol corresponds ...
<p>The variance explained by each principal coordinate axis is shown in parentheses. Datasets were s...
<p>(a) Hierarchical clustering analysis plot. The height represents the Euclidean distance; (b) Prin...
<p>The table presents the Pearson correlation coefficient between the trajectories of the two princi...
<p>Geographical regions having similarity in patterns of spoligotypes tend to clusters together.</p
<p>Principal Component Analysis of Fourier coefficients: scatter plots of PC1 versus PC2 and PC2 ver...
<p>A. Correlation circle of the variables used for the PCA, projected on the first two components. B...
A to C show the results of the PCA based on the 2D plane corresponding to the first 2 axes. D to F s...
<p>A, B and C: Hyperplane between the first and second principal components (PC1 and PC2, respective...
<p>Ellipsoids represent the 95% confidence interval and are a measure for the distance of relationsh...
<p>Principal coordinate analyses (PCA) were performed according to A.) <i>F</i><sub>ST</sub>, B.) <i...
<p>Samples are projected onto the plane formed by the first two principal axes. The first factor exp...
Gower and Krzanowski (1999) described the analysis of a multivariate dataset that violated the assum...
<p>The variance explained by each principal coordinate axis is shown in parentheses. Datasets were s...
A) PCA carried out on full dataset. B) standard deviations of first 10 PCs indicate that the first P...
<p>Scatter plot of individuals, showing the first two principal components. Each symbol corresponds ...
<p>The variance explained by each principal coordinate axis is shown in parentheses. Datasets were s...
<p>(a) Hierarchical clustering analysis plot. The height represents the Euclidean distance; (b) Prin...
<p>The table presents the Pearson correlation coefficient between the trajectories of the two princi...
<p>Geographical regions having similarity in patterns of spoligotypes tend to clusters together.</p
<p>Principal Component Analysis of Fourier coefficients: scatter plots of PC1 versus PC2 and PC2 ver...
<p>A. Correlation circle of the variables used for the PCA, projected on the first two components. B...
A to C show the results of the PCA based on the 2D plane corresponding to the first 2 axes. D to F s...
<p>A, B and C: Hyperplane between the first and second principal components (PC1 and PC2, respective...