Nonparametric geostatistical risk mapping

作者：Fernandez Casal Ruben; Castillo Paez Sergio; Francisco Fernandez Mario^*

来源：Stochastic Environmental Research and Risk Assessment, 2018, 32(3): 675-684.

DOI：10.1007/s00477-017-1407-y

• Local linear regression
• Nonparametric estimation
• Kriging
• Bias-corrected variogram estimation
• Bootstrap

In this work, a fully nonparametric geostatistical approach to estimate threshold exceeding probabilities is proposed. To estimate the large-scale variability (spatial trend) of the process, the nonparametric local linear regression estimator, with the bandwidth selected by a method that takes the spatial dependence into account, is used. A bias-corrected nonparametric estimator of the variogram, obtained from the nonparametric residuals, is proposed to estimate the small-scale variability. Finally, a bootstrap algorithm is designed to estimate the unconditional probabilities of exceeding a threshold value at any location. The behavior of this approach is evaluated through simulation and with an application to a real data set.

• 出版日期2018-3