A Directionally Varying Change Points Model for Quantifying the Impact of a Point Source View Full Text


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Article Info

DATE

2021-08-04

AUTHORS

Jiafang Song, Joshua L. Warren

ABSTRACT

Point sources in spatially referenced data can impact outcomes in surrounding locations (e.g., a factory that emits air pollution). Previous statistical methods have sought to describe the non-stationary correlation induced by the presence of a point source, with fewer attempting to quantify its overall impact. We introduce directionally varying change points (DVCP), a model that aims to estimate the magnitude of the impact of a point source as well as its range of influence across the spatial domain. DVCP allows for a unique change point parameter, describing the range of influence of a point source, at every angle extending from the source and uses a Gaussian process with directionally defined correlation function to facilitate estimation of the parameters. The Gaussian predictive process approximation is used for fitting the model to large datasets. Through simulation, we show that DVCP can easily accommodate a wide range of shapes defining the range of influence. We apply DVCP to better understand spatial patterns of ambient PM2.5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{2.5}$$\end{document} concentrations and issues related to environmental inequity in California and Colorado. The method is available in the R package DVCP.Supplementary materials accompanying this paper appear online. More... »

PAGES

46-62

References to SciGraph publications

  • 2020-07-03. A Nonstationary Spatial Covariance Model for Processes Driven by Point Sources in JOURNAL OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL STATISTICS
  • 2010-01-28. A Spatio-Temporal Downscaler for Output From Numerical Models in JOURNAL OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL STATISTICS
  • 2012-07-11. A note on a non-stationary point source spatial model in ENVIRONMENTAL AND ECOLOGICAL STATISTICS
  • 2020-03-17. Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions in JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY
  • 2011-06-09. On the Validity of Commonly Used Covariance and Variogram Functions on the Sphere in MATHEMATICAL GEOSCIENCES
  • 2011-06-10. The origins of the Gini index: extracts from Variabilit√† e Mutabilit√† (1912) by Corrado Gini in THE JOURNAL OF ECONOMIC INEQUALITY
  • 2018-08-03. Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis in BMC MEDICINE
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    URI

    http://scigraph.springernature.com/pub.10.1007/s13253-021-00466-y

    DOI

    http://dx.doi.org/10.1007/s13253-021-00466-y

    DIMENSIONS

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