A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds a certain threshold value is proposed. The method consists of a bootstrap algorithm that combines conditional simulation techniques with nonparametric estimations of the trend and the variability. The nonparametric local linear estimator, considering a bandwidth matrix selected by a method that takes the spatial dependence into account, is used to estimate the trend. The variability is modeled estimating the conditional variance and the variogram from corrected residuals to avoid the biasses. The proposed method allows to obtain estimates of the conditional exceedance risk in non-observed spatial locations. The performance of the approach is analyzed by simulation and illustrated with the application to a real data set of precipitations in the USA.Supplementary materials accompanying this paper appear on-line.

提出了一种非参数程序来估计非平稳地质统计过程超过某个阈值的条件概率。该方法由引导算法组成，该算法将条件模拟技术与趋势和变异性的非参数估计相结合。非参数局部线性估计器，考虑通过考虑空间依赖性的方法选择的带宽矩阵，用于估计趋势。对变异性进行建模，根据校正残差估计条件方差和变异函数以避免偏差。所提出的方法允许获得对未观察到的空间位置的条件超标风险的估计。