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Distribution of an angle between 3 normally distributed 2D points

Mathematics Asked by simejanko on December 25, 2021

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Given 3 normally distributed points in 2D space, what would the distribution of the angle $alpha$ between the three points be & can it be reasonably well approximated with a (circular) normal distribution.

In my particular case, I have an additional assumption that the covariance matrices are limited to the multipliers of the identity matrix $I_2$, which may simplify the problem.

$A sim N(mu_A, sigma_A * I_{2})$

$B sim N(mu_B, sigma_B * I_{2})$

$C sim N(mu_C, sigma_C * I_{2})$

$alpha sim ?$

I’d be happy with an approximate/engineered solution, could some additional assumptions simplify the problem further?

I don’t have much of a maths background, so my first engineered approximation was to sample the said distribution and infer circular normal distribution parameters that way. The problem with using this approach in practice is its poor computational performance.

One Answer

Let us treat $a=mu_A,b=mu_B,c=mu_C$ as complex numbers. Then we are interested in the random variable that is $Imlogfrac {(a+sigma_AX_A)-(b+sigma_BX_B)}{(c+sigma_C X_C)-(b+sigma_B X_B)}$ where $X_A,X_B,X_C$ are independent standard complex Gaussians (mean $0$, covariance $I_2$). The general case looks rather hopeless, but when $sigma$'s are small compared to the distances, we can linearize and get $$ Imleft{logfrac{a-b}{c-b}+frac{sigma_A}{a-b}X_A-frac{sigma_C}{c-b}X_C -sigma_Bleft[frac1{a-b}-frac1{c-b}right]X_Bright} $$ The first term is just the angle $alpha_0$ the means make and the sum of the last three terms is a complex Gaussian with $0$ mean and the covariance $sigma I_2$ where $$ sigma^2=sigma_A^2frac{1}{|a-b|^2}+sigma_C^2frac1{|c-b|^2}+sigma_B^2left|frac 1{a-b}-frac 1{c-b}right|^2 $$ (everything is measured in radians, of course). The projection to the imaginary axis yields the $N(alpha_0,sigma)$ normal law for the angle you are interested in.

This approximation breaks down for large variances, of course, so you may want to experiment a bit to see what the limitations are.

Answered by fedja on December 25, 2021

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