Sampling of a gaussian distribution

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SUMMARY

This discussion focuses on sampling a Gaussian distribution within a 3D data cube, specifically analyzing the property A, which is modeled as a Gaussian variable with mean m and variance σ². The function A(x,y,z) is defined as A(x,y,z)=f(d(x,y,z))e^(-(X-m)²/(2σ²)), where X is a random number. The conversation emphasizes the implications of dividing the 3D cube into boxes of size ΔX and the role of the function f in the context of Monte Carlo simulations for estimating A.

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matteo86bo
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I have a 3d data cube. For every point I measure the property A which is a gaussian variable of mean m and variance s and it's also a function of the density d at every point.
<br /> <br /> A(x,y,z)=f(d(x,y,z))e^(-(X-m)^2/(2\sigma^2))<br /> <br />

X is a random number.

Now let's say I want to sample the distribution. I mean, I divide my 3d cube in boxes of size delta X.

What happen to the function f?
 
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I'll assume the points are chosen from a Gaussian. If this is a Monte Carlo simulation, then to get an estimate for A, evaluate f.
 

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