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A hierarchical Bayesian model is developed for predicting monthly residential per capita electricity consumption at the state level across the USA. The summer period is selected to target cooling requirements that are generally directly associated with electricity use compared with winter heating requirements that are derived from a mix of energy sources that has changed over time. Historical monthly...
Although the relationships between meteorological conditions and waterway bacterial contamination are being better understood, statistical models capable of fully leveraging these links have not been developed for highly urbanized settings. We present a hierarchical Bayesian regression model for predicting transient fecal indicator bacteria contamination episodes in urban waterways. Canals, creeks,...
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