Estimating Relative Density on a Metric Space

James MacQueen

Let X1, X2, …, be stationary and ergodic random variables with values in a metric space M with distance d, let P(A) = P(Xn in A) and let S(x,r)) > 0 if r > 0, and suppose also that for x in M0, P(S(s,r)) is continuous in x and is differentiable in r for r >= 0, and with a positive derivative for all r in a neighborhood of 0. Consider the set M* of pairs (x,y) such that both x and y are in M0 and limr->0P(S(x,y)) exists and is a finite positive number R(x,y). Then R(x,y) is called the relative density of P for the pair x,y.

The differentiability condition is essentially the same as required for P to have a positive density in the Euclidean case. Note there may be pairs of elements (x,y) such that limr>0P(S(x,r))/P(S(y,r)) fails to exist, is zero, or is positive infinity. For example, if P on the square [0,1]X[0,1] concentrates a total probability of .5 uniformly on the line x = y, 0 x,y x = y is in M* and so is the square excepting the line. But a pair with one element on the line and the other gives a limit of 0 or positive infinity depending which element appears in the numerator (or denominator). This kinds of measures may be of considerable interest and examples where they arise can be given.

2003-09-01