Nonstationary spatiotemporal Bayesian data fusion for pollutants in the near‐road environment-Reference-Cited by-同舟云学术

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Nonstationary spatiotemporal Bayesian data fusion for pollutants in the near‐road environment

Published:2019-06-09 Issue:7 Volume:30 Page:
ISSN:1180-4009
Container-title:Environmetrics
language:en
Short-container-title:Environmetrics

Author:

Gilani O.¹,Berrocal V. J.²,Batterman S. A.³

Affiliation:

1. Department of MathematicsBucknell University Lewisburg Pennsylvania

2. Department of BiostatisticsUniversity of Michigan School of Public Health Ann Arbor Michigan

3. Department of Environmental Health SciencesUniversity of Michigan School of Public Health Ann Arbor Michigan

Funder

Health Effects Institute

Publisher

Wiley

Subject

Ecological Modeling,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2581

Reference45 articles.

1. High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data

2. Factors affecting pollutant concentrations in the near-road environment

3. Temporal variation of traffic on highways and the development of accurate temporal allocation factors for air pollution analyses

4. A bivariate space–time downscaler under space and time misalignment

5. A Spatio-Temporal Downscaler for Output From Numerical Models

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1. Accounting for survey design in Bayesian disaggregation of survey-based areal estimates of proportions: An application to the American Community Survey;The Annals of Applied Statistics;2022-12-01

2. Data fusion with Gaussian processes for estimation of environmental hazard events;Environmetrics;2020-10-20

3. Quantifying the impact of the modifiable areal unit problem when estimating the health effects of air pollution;Environmetrics;2020-08-03

4. A comparison of statistical and machine learning methods for creating national daily maps of ambient PM2.5 concentration;Atmospheric Environment;2020-02

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