We investigate whether a class of trend models, which decompose time series into an underlying and transitory component, with various error term structures can improve upon the forecast performance commonly used models when forecasting consumer price index (CPI) inflation in Australia. The main result is that tend to provide more accurate point density forecasts at medium long horizons compared...

Current multi-temporal interferometric Synthetic Aperture Radar (MTInSAR) datasets cover long time periods with regular temporal sampling. This allows high-rate and non-linear trends to be observed, which typically characterize pre-failure warning signals. In order fully exploit the content of MTInSAR products, methods are needed for automatic identification relevant changes along displacement ...