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Three points A, B, C are randomly distributed on a plane, with the following constrainsts:
What would be the average (expected value) for the distance r between A and C?
Of course the maximum is r = p + q. But what is the average? You can imagine A, B and C as being three cities. Without loss of generality, you can assume that A and B are fixed, and only C is random.
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So, I took the integral from 0 to 2pi of p^2 + q^2 - 2*p*q*cos(t) and normalized by 2pi. You end up with r^2 = p^2 + q^2 as the average. So, r = sqrt(p^2+q^2).
Keith Portman
Interesting, the average corresponds to the case where the triangle is right.
Hi Keith,
If p = q your solution would mean E[r] =p * sqrt(2) where I find E[r] = p*(4/pi)
please see my post below .
I did not try to solve it myself, but I thought that the solution would imply a number like pi rather than SQRT(2). In short, this problem can be used (with p = q = 1) in Monte Carlo simulations to estimate pi.
Without integration obviously Mean(cos(x)) = 0
I did the integral of x from 0 to pi of sqrt( p^2 + q^2 -2p*qcos(x))/pi
The answer comes down to an elliptic integral. The expectation of r is given by:
E[r] = 2 * (p+q) * Elliptic(4pq/((p+q)^2 ) / pi
Without loss of generality lets assume that p < q. Then E[r] is approximately
E[r] = (p+q) * ( 1- (p/q) + (5/4)(p/q)^2 - (5/4)(p/q)^3 + (81/128)(p/q)^4 )
and when p and q are the same E[r] -> p*(4/pi) which is approximately p*(81/64) according to the formula above
and when p is much smaller than q we have
E[r] -> p+q
and as p ->0 then we have E[r] -> q
Osorio Meirelles
A better approximation with more terms:
E[r] = (p+q) * ( 1- (p/q) + (5/4)(p/q)^2 - (5/4)(p/q)^3 + (81/64)(p/q)^4 )
- (81/64)*(p/q)^5 + (325/256)*(p/q)^6 -(325/256)*(p/q)^7 + (20825/32768)*(p/q)^8 )
Very nice question,
but it is hard to answer without knowing how is the distribution of 'random' points.
considering it has 3 deg of freedom and 2 bounds, without loss of generality we can we can map e.g. B to the origin and A on the x axis. now C is bound to lay on the circle of radius q around the origin.
To successfully approach this problem one needs to know the distribution of q.
Assuming P(w) the probability density of C laying so that ABC forms an angle w and applying the Law of Cosine.
the solution is given by r^2 = \Integral_0_{2\pi} [p^2+q^2-2p*q*cos(w)] P(dw)
the case of P(w) uniform is given below.
The mean of both p and q will be equal (from the same Wald distribution), which means r can be considered the mean chord length of a circle. Chord length is easy to calculate, and the angle ABC exists as a uniform distribution between 0 and 180 degrees (with mean 90 degrees).
Or r = sqrt(2p^2)
Osorio has it right for an otherwise uniformly distributed point set. The average of r in that case is a complete elliptic integral of the second kind. A reasonably well-converging approximation is
<r> = (p + q) * [1 - Sum_(k=1)^inf ((2k-1)!!/2k!!)^2 * m^k/(2k-1)], where m = 4pq/(p+q)^2.
The first few terms are: (p + q) * [1 - (1/4)m - (3/64)m^2 - (45/2304)m^3 - ...]
For an otherwise non-uniformly distributed point set, Davide has the right idea.
At least two responses implied a claim that E(r^2)=[E(r)]^2, which is clearly not true, otherwise all variances would have to equal zero (!).
This integral appears often in tactical naval calculations when one is trying to understand how a ship's speed (p) affects its rate of encountering ships at another speed (q) in random orientations.