Generate Elliptical Distribution from Box-Muller Transform

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SUMMARY

The Box-Muller Transform can be effectively utilized to generate an elliptical distribution by applying different standard deviations (sigma_x and sigma_y) to the two output variables. By transforming standard normally distributed variables into a random variable Z with a specified mean (u) and standard deviation (sigma), one can achieve the desired elliptical shape on the x/y plane. The transformation can be expressed as Z = sigma*X + u, where X is the standard normal variable generated by the Box-Muller method.

PREREQUISITES
  • Understanding of the Box-Muller Transform
  • Familiarity with Gaussian distributions
  • Knowledge of statistical transformations
  • Basic programming skills for implementing pseudo code
NEXT STEPS
  • Implement the Box-Muller Transform in Python or R
  • Explore the concept of elliptical distributions in statistics
  • Learn about random variable transformations in probability theory
  • Study the application of Gaussian distributions in data modeling
USEFUL FOR

Data scientists, statisticians, and programmers interested in generating random variables with specific distributions for simulations or modeling purposes.

ireland01
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Can i use box muller transform to generate a distribution with two different sigma (i.e. sigma_x and sigma_y)?

I want to generate a random gaussian angle (C) relative to z axis on circle plane, then set the angle relative to the x, A and y axis, B, wrt to the original angle.
However, I want the output to be elliptical on x/y plane...

Some pseudo code would help.
 
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If X is normal with zero mean and std dev = 1, then you can transform it into a random variable Z with mean u and std dev sigma as follows:

Z = sigma*X + u

The Box-Muller transform gives you two random variables which are standard normally distributed iirc, so just apply the above transformation to each.
 

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