<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Abdalla N</submitter><funding>NIEHS NIH HHS</funding><funding>NIOSH CDC HHS</funding><pagination>818-827</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6093467</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>62(7)</volume><pubmed_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.</pubmed_abstract><journal>Annals of work exposures and health</journal><pubmed_title>Coastline Kriging: A Bayesian Approach.</pubmed_title><pmcid>PMC6093467</pmcid><funding_grant_id>R01 ES027027</funding_grant_id><funding_grant_id>R01 OH010093</funding_grant_id><pubmed_authors>Banerjee S</pubmed_authors><pubmed_authors>Ramachandran G</pubmed_authors><pubmed_authors>Stewart PA</pubmed_authors><pubmed_authors>Abdalla N</pubmed_authors><pubmed_authors>Stenzel M</pubmed_authors></additional><is_claimable>false</is_claimable><name>Coastline Kriging: A Bayesian Approach.</name><description>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.</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Aug</publication><modification>2021-02-21T08:17:44Z</modification><creation>2019-08-16T07:00:18Z</creation></dates><accession>S-EPMC6093467</accession><cross_references><pubmed>30052748</pubmed><doi>10.1093/annweh/wxy058</doi></cross_references></HashMap>