<p>The figure shows a biplot a PCA performed on the EsSense and PrEmo emotions. Every data point represents all rated emotions per method that were rated by a participant on a single product. The data points are colored based on empirical choice; chosen products are colored green and not chosen products are colored red. In blue we plotted the loadings of all emotion variables.</p
<p>Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for...
(A) shows the explained variance as a function of the number of PCA components. We also plot the rat...
<p>PCA using normal esophagus (n = 25) and EoE samples (n = 11 untreated and n = 26 treated). The bi...
Orthal cases 4) in M1 5) in M2 and 6) in M3. The loadings for each variable are coloured according s...
<p>A: whole experiment dataset; B: Tendril dataset; C: Inflorescence dataset. Percent of variation e...
<p>Note: Each colored point represents a sample. The first, second and third principal components ar...
<p>PCA biplot of the calculated scores and loadings for the soil experimental samples.</p
PBMC profiles obtained are shown in (A) and (B). Serum data are shown in (C) and (D). Individual plo...
Fixes for biplot when choosing different PC to plot. New parameter for biplot, to color the arrow: m...
<p>(A) The score plot showing the separation between the Case group(X) and the Control group (o) (B)...
<p>We used PCA to describe dewlap and ventral patch hue, chroma, and brightness as an independent co...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
<p>PCA scores plot obtained from analysis of gene expression profiles. Proportion of the variance ex...
The figure shows the first two principal components after merging the acquired datasets. The samples...
<p>of microarray expression data based on complete data set. Red nodes represent control subjects, b...
<p>Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for...
(A) shows the explained variance as a function of the number of PCA components. We also plot the rat...
<p>PCA using normal esophagus (n = 25) and EoE samples (n = 11 untreated and n = 26 treated). The bi...
Orthal cases 4) in M1 5) in M2 and 6) in M3. The loadings for each variable are coloured according s...
<p>A: whole experiment dataset; B: Tendril dataset; C: Inflorescence dataset. Percent of variation e...
<p>Note: Each colored point represents a sample. The first, second and third principal components ar...
<p>PCA biplot of the calculated scores and loadings for the soil experimental samples.</p
PBMC profiles obtained are shown in (A) and (B). Serum data are shown in (C) and (D). Individual plo...
Fixes for biplot when choosing different PC to plot. New parameter for biplot, to color the arrow: m...
<p>(A) The score plot showing the separation between the Case group(X) and the Control group (o) (B)...
<p>We used PCA to describe dewlap and ventral patch hue, chroma, and brightness as an independent co...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
<p>PCA scores plot obtained from analysis of gene expression profiles. Proportion of the variance ex...
The figure shows the first two principal components after merging the acquired datasets. The samples...
<p>of microarray expression data based on complete data set. Red nodes represent control subjects, b...
<p>Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for...
(A) shows the explained variance as a function of the number of PCA components. We also plot the rat...
<p>PCA using normal esophagus (n = 25) and EoE samples (n = 11 untreated and n = 26 treated). The bi...