Thanks so much for the elaborated explanation as the response given by @DanielAsarnow. Your reply and also the video tutorial was also helpful to understand the paper conceptually better.
With that, I understand your statement below and agree with it.
> Thus, it is not fair to say that the most ‘most dominant/variable motion’ (i.e., one that the structure actually undergoes) is defined by the first variation component.
But I was trying to interpret the scatter plot (attached here again) to tell the variability, not necessarily by order of component 0 and component 1 and so on.
And the statement below is what I found from the 3DVA tutorial and sounds very similar to what I understood in the paper.
> (3DVA tutorial) …The figure below shows the reaction coordinate distribution of particles, as scatter plots between adjacent pairs of components (0 vs 1, 1 vs 2, 2 vs 3, etc). Clearly, the first component (0) has the most variability.
If I understand correctly, running 3DVA with K=3 will yield the top three variability components that explain the most variability in the data, and one could think that the component showing more (or the most) large variance explains the most variability in the data.
I wonder if one could help me to interpret the scatter plot (attache above) and please correct me if my interpretation; component 0 in the attached scatter plot has the most variability, is wrong.
Min Woo Sung