10 questions linked to/from Visualizing a million, PCA edition
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### Are there examples of more informative PCA plots? [duplicate]

I am often disappointed with PCA plots in the scientific literature. Typically PCA plots do not provide a breakdown of the variables and their weights, just something like PCA1 (70% variance explained)...
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### How to interpret ggbiplot() visualization of PCA in R? [duplicate]

To apply and visualize PCA in R often ggbiplot() is used. What is the meaning of this plot ? Why it is useful for PCA ? We can consider this example: https://tgmstat.wordpress.com/2013/11/28/...
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### Visualizing and interpreting principal components [duplicate]

I have performed principal component analysis (PCA) in Matlab via [U,S,V] = svd(X) Now I have to show the principal directions of the considered principal ...
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### What are the differences between Factor Analysis and Principal Component Analysis?

It seems that a number of the statistical packages that I use wrap these two concepts together. However, I'm wondering if there are different assumptions or data 'formalities' that must be true to use ...
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### Positioning the arrows on a PCA biplot

I am looking to implement a biplot for principal component analysis (PCA) in JavaScript. My question is, how do I determine the coordinates of the arrows from the $U,V,D$ output of the singular vector ...
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### What is the difference between "loadings" and "correlation loadings" in PCA and PLS?

One common thing to do when doing Principal Component Analysis (PCA) is to plot two loadings against each other to investigate the relationships between the variables. In the paper accompanying the ...
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### Post-hoc tests for MANOVA: univariate ANOVAs or discriminant analysis?

I am using a MANOVA test to compare nine different dependent variables (from neuropsychological and neuropsychiatric assessment) between three groups. The output shows a significant influence from ...
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### Eigenvalues of correlation matrices exhibit exponential decay

I have a data-set of $P$ samples of size $N$, and noticed that the eigenvalues of the correlation matrices $A^TA$, when presented in descending order, can in many cases be described as an exponential ...
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