Structural changes often occur in economics and finance due to preferences, technologies, institutional arrangements, policies, crises, etc. Improving forecast accuracy of economic time series with structural is a long-standing problem. Model averaging aims at providing an insurance against selecting poor model. All existing model approaches the literature are designed constant (non-time-varyin...

Averaging neural network weights sampled by a backbone stochastic gradient descent (SGD) is simple-yet-effective approach to assist the SGD in finding better optima, terms of generalization. From statistical perspective, weight-averaging contributes variance reduction. Recently, well-established (SWA) method was proposed, which featured application cyclical or high-constant (CHC) learning-rate ...

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...