Spatial models in retailing allow for correlations among purchase decisions from consumers within predefined geographic areas. The purpose of these models is to control for unobserved demand side effects at the regional-level (e.g., a neighborhood), but they typically ignore synergies among...

We propose the use of Bayesian estimation of risk preferences of individuals for applications of behavioral welfare economics to evaluate observed choices that involve risk. Bayesian estimation provides more systematic control of the use of informative priors over inferences about risk...

This paper proposes a Bayesian estimation framework for panel-data sets with binary dependent variables where a large number of cross-sectional units is observed over a short period of time, and cross-sectional units are interdependent in more than a single network domain. The latter provides...

In this research, a Bayesian web-based Decision Support System (DSS) was designed and developed to assist various stakeholders in improving biophysical and socio-economic conditions in a stressed and fragile watershed by systematically presenting the watershed characteristics, introducing...

Based on Bayesian model averaging (BMA), the suitability and characteristics of the BMA model for forecasting 2-m temperature in Xinjiang of China was analyzed by using the forecast results of the Desert Oasis Gobi Regional Analysis Forecast System (DOGRAFS) and Rapid-refresh Multiscale Analysis...

Seabirds are bioindicators of marine ecosystems and one of the world's most endangered avian groups. The creation of marine protected areas plays an important role in the conservation of marine environment and its biodiversity. The use of top predators distributions, as seabirds, for the...

Conventional multi-task Bayesian compressive sensing methods, which compute the sparse representations of signals with a group sparse pattern, generally ignore the inner sparse structures of signals and/or their statistical correlations. These structures are naturally exhibited among clustered...

The optimal structure of a sinusoidal wavy plate fin heat sink with crosscut ( SWHS-WC) is determined by an efficient intelligent optimization method based on the Bayesian Optimization (BO) algorithm. The comprehensive thermal performance factor (TPF) is the objective function to associate with...

Unplanned nuclear power plant (NPP) reactor trips due to operator error have frequently occurred during start-up and shutdown operations on account of operator workload and fatigue. Despite the need for efforts to reduce such human errors through human reliability analysis (HRA), most existing...

Multi-objective Bayesian optimization (MOBO) is an efficient and robust optimization framework for expensive functions. In this work, we use MOBO to optimize the free parameters of a high-order nonlinear weighted essentially non-oscillatory (WENO) reconstruction scheme to devise a model for...