Simplex Point Picking: Distribution of x_i Over (0,1)

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The discussion focuses on the challenge of selecting a uniform probability distribution from the simplex defined by the condition that the coordinates sum to one. A method proposed involves selecting random values from a uniform distribution over (0,1) and transforming them using logarithmic functions. Participants explore the probability distribution of the coordinates and the relationship between the volume of the simplex and the desired probability density function (p.d.f). Clarifications are made regarding terminology, specifically distinguishing between hyperpyramids and simplices. The final suggestion emphasizes the need for a ratio of volumes to accurately represent the p.d.f. for the coordinates in the simplex.
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I have an application where I need to pick a probability distribution (x_{1},\ldots,x_{n}) at random and uniformly from the simplex of all points for which the coordinates add up to 1, i.e. \sum_{i=1}^{n}x_{i}=1. Surprisingly, I didn't find much about simplex point picking on the internet, but http://en.wikipedia.org/wiki/User:Skinnerd/Simplex_Point_Picking appears to address this issue. Skinnerd suggests to pick individual members of (y_{1},\ldots,y_{n}) randomly from a uniform distribution over the interval (0,1) and then take x_{i}=\frac{\ln{}y_{i}}{\sum{}\ln{}y_{i}}. So far so good (although, why does he need the minus sign in his x_{i}=-\ln{}y_{i}?).

My question is: what is the distribution of x_{i} over the interval (0,1), i.e. what is the probability P(a<x<b) that one of these coordinates is in (a,b)\subseteq{}(0,1)?
 
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If Xi = x, that leaves a hyperpyramid ##\Sigma_{i\neq i}X_j = 1 - x##. Can't you make the p.d.f of Xi proportional to the volume of that?
 
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volume of n-dimensional simplex

Great idea! I am a little confused about terminology. Hyperpyramid at http://physicsinsights.org/pyramids-1.html seems to mean that the height of the pyramid is the same as the side of the base -- which is not what we want here. We want something more like a generalization for n dimensions of a pentatope, see http://mathworld.wolfram.com/Pentatope.html. Mathworld advises on the volume of a simplex in n dimensions at http://mathworld.wolfram.com/Cayley-MengerDeterminant.html. What haruspex is suggesting, as I see it, is that

P(0<x<b)=S(\sqrt{2})-S(\sqrt{2}(1-b))

where S(z) is the volume of a simplex in n dimensions whose side length is z. In our case, z=\sqrt{2} because x_{1}+\ldots{}+x_{n}=1.
 
stlukits said:
Great idea! I am a little confused about terminology. Hyperpyramid at http://physicsinsights.org/pyramids-1.html seems to mean that the height of the pyramid is the same as the side of the base -- which is not what we want here. We want something more like a generalization for n dimensions of a pentatope, see http://mathworld.wolfram.com/Pentatope.html.
Seems that simplex is the word I should have used.
Mathworld advises on the volume of a simplex in n dimensions at http://mathworld.wolfram.com/Cayley-MengerDeterminant.html. What haruspex is suggesting, as I see it, is that

P(0<x<b)=S(\sqrt{2})-S(\sqrt{2}(1-b))

where S(z) is the volume of a simplex in n dimensions whose side length is z. In our case, z=\sqrt{2} because x_{1}+\ldots{}+x_{n}=1.
Not sure that's quite what I was saying. For a start, there should be a ratio of volumes in there.
I think I'm saying the p.d.f., f(x) = Sn-1((1-x)√2)/Sn(√2), or maybe the subscripts should be n, n+1. You'd then to integrate that to get the interval probability.
 
Yes, indeed, it should be a ratio, not a difference. Thanks, haruspex!
 
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