One approach to resolving this issue has been developing models to predict local PM 2.5 , NO 2 , and ozone in unmonitored areas based on satellite, ...
May 29, 2018 · We have developed a flexible R package that allows for environmental health researchers to design and train spatio-temporal models capable of ...
Sabath BM, Di Q, Braun D, Dominici F, Choirat C. airpred: A Flexible R Package Implementing Methods for Predicting Air Pollution. IEE DSAA Accepted. 2018.
A flexible R package that allows environmental health researchers to design and train spatio-temporal models capable of predicting multiple pollutants, ...
Large epidemiological studies have shown that exposure to air pol- lution, in particular fine particulate matter (PM2.5), is harmful to human health.
... They model the main air pollutants spatial variability at a given time using diverse datasets including monitoring stations measurements, satellite-based ...
We have developed a flexible R package that allows for environmental health researchers to design and train spatio-temporal models capable of predicting ...
Missing: Airpred: | Show results with:Airpred:
Airpred: A Flexible R Package Implementing Methods for Predicting Air Pollution. M. Sabath, Q. Di, D. Braun, J. Schwartz, F. Dominici, and C. Choirat.
airpred: A Flexible R Package Implementing Methods for Predicting Air Pollution ... Fine particulate matter (PM 2. 5 ) is one of the criteria air pollutants ...
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Airpred: A Flexible R Package Implementing Methods for Predicting Air Pollution. DSAA 2018: 577-583. [i1]. view. electronic edition @ arxiv.org (open access) ...