
arXiv: 1103.5884
In this paper, we give sufficient conditions to establish central limit theorems for boundary estimates of Poisson point processes. The considered estimates are obtained by smoothing some bias corrected extreme values of the point process. We show how the smoothing leads Gaussian asymptotic distributions and therefore pointwise confidence intervals. Some new unidimensional and multidimensional examples are provided.
[STAT.ME] Statistics [stat]/Methodology [stat.ME], Inference from spatial processes, functional estimate, Mathematics - Statistics Theory, Poisson process, Statistics Theory (math.ST), 510, Extreme value theory; extremal stochastic processes, boundary estimation, Asymptotic properties of nonparametric inference, FOS: Mathematics, Nonparametric estimation, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
[STAT.ME] Statistics [stat]/Methodology [stat.ME], Inference from spatial processes, functional estimate, Mathematics - Statistics Theory, Poisson process, Statistics Theory (math.ST), 510, Extreme value theory; extremal stochastic processes, boundary estimation, Asymptotic properties of nonparametric inference, FOS: Mathematics, Nonparametric estimation, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
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