What are the components of Davidski's G25 calculator, in order?
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What are the components of Davidski's G25 calculator, in order?
does it mean anything if you have identical coordinates with an individual or population? for example PC2.
also, up to which PC are they relevant? the first ones capture most of the differences, right?
also, since PCA plots only use PC1 and PC2, how much is lost? do people give too much credit to PCA plots (because they only have PC1 and PC2, in the end)?
But each coordinate is related to one ethnic group or origin, isnīt it?
And we donīt know exactly to wich origin is related every coordinate, although I have some of them more or less identified.
Anyway, itīs ok donīt know exactly which origins is related every coordinate, so some people cannot change them in order to fake his results.(as it happens with K13 coordinates and others).
I just read that he's taking out modern samples and just using ancient samples. I disagree with this. There should be a modern sample, even if people get mad. Even if some people may not match because of 'personal identification,' with enough samples, these false samples will be averaged out.
As far as I know this is SmartPCA on raw dataset. https://github.com/chrchang/eigensoft/wiki/smartpca
Vbknethio did it for test (G30) and there is thread about it here.
But theoretically Davidski could make K25 calculator and could make PCA in PAST on it's oracle ( I did it for K36 but additionally make few other conversions to hide real components). Such method would be faster when he wanted to sell coordinates from obvious reasons...
But in such case principal components couldn't be just calculator components (check what is PCA on wikipedia or elswhere) and certainly not in that order like originally. Everyone can test and make PCA on K13 or K15 oracle in PAST for example. So still you can't infer from principal component what was original calc component for first column, or second and so on.
In Vahaduo / NMonte nothing is lost. Calculation is on 25 PCs. Yes, first principal components are most important always. You can easily dismiss last 5 I think... Someone can make sheet with only 20 values and check.
But you lost 23 PCs when you make PCA plot. Or 22 if you make 3D plot.
Interesting case, you have such example?Quote:
does it mean anything if you have identical coordinates with an individual or population? for example PC2.