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http://dx.doi.org/10.5351/KJAS.2016.29.2.345

Analyzing landslide data using Cauchy cluster process  

Lee, Kise (Department of Statistics, Inha University)
Kim, Jeonghwan (Department of Statistics, Inha University)
Park, No-wook (Department of Geoinformatic Engineering, Inha University)
Lee, Woojoo (Department of Statistics, Inha University)
Publication Information
The Korean Journal of Applied Statistics / v.29, no.2, 2016 , pp. 345-354 More about this Journal
Abstract
Inhomogeneous Poisson process models are widely applied to landslide data to understand how environmental variables systematically influence the risk of landslides. However, those models cannot successfully explain the clustering phenomenon of landslide locations. In order to overcome this limitation, we propose to use a Cauchy cluster process model and show how it improves the goodness of fit to the landslide data in terms of K-function. In addition, a numerical study is performed to select the optimal estimation method for the Cauchy cluster process.
Keywords
landslide; point pattern data; Poisson process; Cauchy cluster process;
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Times Cited By KSCI : 1  (Citation Analysis)
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