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We present a method for estimating the edge of a two-dimensional bounded set, given a finite random set of points drawn from the interior. The estimator is based both on a Parzen-Rosenblatt kernel and extreme values of point processes. We give conditions for various kinds of convergence and asymptotic normality. We propose a method of reducing the negative bias and edge effects, illustrated by some simulations.
We present a method for estimating the edge of a two-dimensional
bounded set, given a finite random set of points drawn from the interior.
The estimator is based both on a Parzen-Rosenblatt kernel and
extreme values of point processes. We give conditions
for various kinds of convergence and asymptotic normality.
We propose a method of reducing the negative bias and edge effects,
illustrated by some simulations.
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