We examined how the addition of spatial correlations to a previously described unified exposure and health outcome modeling framework affects estimates of exposure response relationships using the substudy data.
This study develops a new modeling framework for estimating the interchange capability between MMGs and a distribution network (DN) to increase the situation awareness of the microgrid operator.
Here, we demonstrate a new Bayesian hierarchical modeling framework for estimating inter-annual variation in vegetation phenology from Landsat time series while controlling for spatial variation.
This finding indicates the utility of our modeling framework for estimating the impact of land use on pedestrian space-time exposure at the block level.
The use of this modeling framework to estimate risks for specific risk groups, defined by (combinations of) specific risk factors, is illustrated.
In this study, we develop a rigorous geostatistical modeling framework to estimate the hypoxic extent in the northern Gulf of Mexico from data collected during midsummer, quasi-synoptic monitoring cruises (1985 2011).
In GTAP modeling framework, welfare change estimates the change in utility due to distortions.
A modeling framework is discussed for estimating fisheries cost data.
The modeling framework is used to estimate the effect of land use, land management, and ecosystem disturbance on C balance in four select vegetation types for the GDS (Fig. 1).
Our modeling framework has been designed to estimate historical as well as current monthly patterns in plant carbon fixation, living biomass increments, nutrient allocation, litter fall and decomposition, long-term decay of downed woody pools, soil CO 2 respiration, and soil nutrient mineralization before, during, and after disturbance events such as wildfires.
