Spatial Prediction of N2O Emissions in Pasture: A Bayesian Model Averaging Analysis

Spatial Prediction of N2O Emissions in Pasture: A Bayesian Model Averaging Analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, dis...

Bayesian Prediction in Spatial Data Analysis

Predicting waste generation using Bayesian model averaging

A prognosis model has been developed for solid waste generation from households in Hoi An City, a famous tourist city in Viet Nam. Waste sampling, followed by a questionnaire survey, was carried out to gather data. The Bayesian model average method was used to identify factors significantly associated with waste generation. Multivariate linear regression analysis was then applied to evaluate th...

Bayesian Averaging, Prediction and Nonnested Model Selection

This paper studies the asymptotic relationship between Bayesian model averaging and postselection frequentist predictors in both nested and nonnested models. We derive conditions under which their difference is of a smaller order of magnitude than the inverse of the square root of the sample size in large samples. This result depends crucially on the relation between posterior odds and frequent...

Efficient Bayesian Model Averaging in Factor Analysis

Although factor analytic models have proven useful for covariance structure modeling and dimensionality reduction in a wide variety of applications, a challenging problem is uncertainty in the number of latent factors. This article proposes an efficient Bayesian approach for model selection and averaging in hierarchical models having one or more factor analytic components. In particular, the ap...