To improve operational efficiencies while providing state of the art healthcare services, hospitals rely on IT enabled physician referral systems (IT-PRS). This study examines learning curves in an IT-PRS setting to determine whether agents achieve performance improvements from cumulative...

The repeated occurrences of interventions in observations make most forecasting models fail to produce appropriate forecasts. The purpose of this study is to propose the adaptive forecasting procedure based on sequential identifications of interventions and adjusting forecast to them in general...

A Bayesian method to detect structural changes in multivariate dynamic linear model is introduced and it is applied to predicting and dating the turns in business cycle. As many researchers use for business cycle analysis, the composite leading index (CLI) and the composite coincident index...

Most forecasting models often fail to produce appropriate forecasts because they are built on the assumption that data is being generated from only one stochastic process. However, in many real world problems, the time series data are generated from one stochastic process initially and then...