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Eigenvectors and eigenvalues, sufficient sampling issues
Doing a principal component analysis (PCA) of a trajectory is easy. And is even easier to prepare nice . . . motions of the solute (see [[Calculation of eigenvalues and eigenvectors]] and [[More on eigenvectors . . . and eigenvalues]]). And if you are not careful, it is just . . .
5K - last updated 2005-10-17 10:59 UTC by server.cluster.mbg.gr

More on eigenvectors and eigenvalues
Calculation of eigenvalues and eigenvectors is the first step for performing a large number of other . . . configurational space. See [[Eigenvectors and eigenvalues, sufficient sampling issues]]. Having a . . . of collective motions == If you do a plot of the eigenvalues (xmgr carma.eigenvalues.dat) you will see . . . (in decreasing order of corresponding eigenvalues). The numbers are the amplitudes with which . . . to the one discussed in [[Eigenvectors and eigenvalues, sufficient sampling issues]]. For example, . . .
6K - last updated 2006-02-22 15:12 UTC by server.cluster.mbg.gr

Tools and methods for analysing MD simulations
Please add other analyses, other methods/programs for performing the same task, etc. * [[Quick view of . . . component analysis]] * [[Calculation of eigenvalues and eigenvectors]] * [[More on eigenvectors . . . and eigenvalues]] * [[Eigenvectors and eigenvalues, sufficient . . .
2K - last updated 2007-02-05 10:15 UTC by server.cluster.mbg.gr

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