Testing the existence of unit root and/or level change is necessary in order to understand the underlying processes of time series. In many studies carried out so far, the focus was only on a single aspect of unit root and level change, therefore limiting a full assess to the given problems. Our...

Testing the existence of unit root and|or level change is necessary in order to understand the underlying processes of time series. In many studies carried out so far, the focus was only on a single aspect of unit root and level change, therefore limiting a full assessment of the given problems....

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...