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I need at least a couple of keywords to get me started and read for my self.

Suppose I have a number $M$ of populations. From each population, I draw $R$ replicas of a parameter vector $\vec x$ of $N$ dimensions. In total, I have $R\times M$ samples of $N$-dimensions each.

I want to see what components of $\vec{x}$ are different across across the populations. I would like a way to detect the most significant variations. Is this possible?

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  • $\begingroup$ Are you using R? $\endgroup$
    – Bruna w
    Nov 22, 2017 at 21:30
  • $\begingroup$ @Brunaw Python :) $\endgroup$
    – a06e
    Nov 22, 2017 at 21:32
  • $\begingroup$ I can't help you them, I use only R ): but I can tell tou that this question might be better answered in Stack Overflow (btw, the answer is yes, it's possible) $\endgroup$
    – Bruna w
    Nov 22, 2017 at 21:38
  • $\begingroup$ @Brunaw Perhaps if you tell me the name of the method, I can look it up. How would you do it in R? $\endgroup$
    – a06e
    Nov 22, 2017 at 21:51

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