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Quasi-plus sampling edge correction for spatial point patterns

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  • Tscheschel, André
  • Chiu, Sung Nok

Abstract

A widely applicable edge correction method for estimating summary statistics of a spatial point pattern is proposed. We reconstruct point patterns in a larger region containing the sampling window by matching sampled and simulated kth nearest neighbour distance distributions of the given pattern and then apply plus sampling. Simulation studies show that this approach, called quasi-plus sampling, gives estimates with smaller root mean squared errors than estimates obtained by using other popular edge corrections. We apply the proposed approach to real data and yield an estimate of a summary statistic that is more plausible than that obtained by a popular edge correction.

Suggested Citation

  • Tscheschel, André & Chiu, Sung Nok, 2008. "Quasi-plus sampling edge correction for spatial point patterns," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5287-5295, August.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:12:p:5287-5295
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    References listed on IDEAS

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    1. Dietrich Stoyan & Helga Stoyan, 2000. "Improving Ratio Estimators of Second Order Point Process Characteristics," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 641-656, December.
    2. S. N. Chiu & D. Stoyan, 1998. "Estimators of distance distributions for spatial patterns," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 52(2), pages 239-246, June.
    3. Dietrich Stoyan, 2006. "On Estimators of the Nearest Neighbour Distance Distribution Function for Stationary Point Processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 64(2), pages 139-150, October.
    4. Tscheschel, A. & Stoyan, D., 2006. "Statistical reconstruction of random point patterns," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 859-871, November.
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    1. Kateřina Koňasová & Jiří Dvořák, 2021. "Stochastic Reconstruction for Inhomogeneous Point Patterns," Methodology and Computing in Applied Probability, Springer, vol. 23(2), pages 527-547, June.

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