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Coastline Kriging: A Bayesian Approach.


ABSTRACT: Statistical interpolation of chemical concentrations at new locations is an important step in assessing a worker's exposure level. When measurements are available from coastlines, as is the case in coastal clean-up operations in oil spills, one may need a mechanism to carry out spatial interpolation at new locations along the coast. In this article, we present a simple model for analyzing spatial data that is observed over a coastline. We demonstrate four different models using two different representations of the coast using curves. The four models were demonstrated on simulated data and one of them was also demonstrated on a dataset from the GuLF STUDY (Gulf Long-term Follow-up Study). Our contribution here is to offer practicing hygienists and exposure assessors with a simple and easy method to implement Bayesian hierarchical models for analyzing and interpolating coastal chemical concentrations.

SUBMITTER: Abdalla N 

PROVIDER: S-EPMC6093467 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Coastline Kriging: A Bayesian Approach.

Abdalla Nada N   Banerjee Sudipto S   Ramachandran Gurumurthy G   Stenzel Mark M   Stewart Patricia A PA  

Annals of work exposures and health 20180801 7


Statistical interpolation of chemical concentrations at new locations is an important step in assessing a worker's exposure level. When measurements are available from coastlines, as is the case in coastal clean-up operations in oil spills, one may need a mechanism to carry out spatial interpolation at new locations along the coast. In this article, we present a simple model for analyzing spatial data that is observed over a coastline. We demonstrate four different models using two different rep  ...[more]

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