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Activity Number: 344
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #312599 View Presentation
Title: Prediction Intervals for Integrals of Random Fields
Author(s): Victor De Oliveira*+ and Bazoumana Kone
Companies: University of Texas at San Antonio and University of Texas at San Antonio
Keywords: Block average ; Bootstrap calibration ; Change-of-support problem ; Geostatistics ; Kriging ; Spatial average
Abstract:

In this work we propose methods to construct prediction intervals for integrals of random fields over bounded regions (called block averages in the geostatistical literature) based on observations at a finite set of sampling locations. For Gaussian random fields we propose two bootstrap calibration algorithms, termed indirect and direct, aimed at improving upon plug-in prediction intervals in terms of coverage probability. For non-Gaussian random fields we propose a semi-parametric bootstrap approach that does not rely on distributional assumptions. Simulation studies are carried out that illustrate the effectiveness of the proposed procedures, and these procedures are applied to estimate spatial averages of chromium and cadmium traces in a potentially contaminated region in Switzerland.


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