In the literature on unobservable component models , three main statistical instruments have been used for signal extraction: fixed interval smoothing (FIS), which derives from Kalman's seminal work on optimal state-space filter theory in the time domain; Wiener-Kolmogorov-Whittle optimal signal...

This book explores globalisation and the war on terror in a world that is becoming increasingly and significantly polarised and in which dialogue is undermined. The authors contend that citizenship does not obey a static definition, and that its meaning is located in changing economic, social...

Purpose – Since the early 1990s there has been a growth in local authorities of risk management. However, despite a range of different strategies, initiatives and practices the issue of financing the risks to which authorities are exposed has remained problematic. The traditional dependence on...

Operational flood forecasting requires accurate forecasts with a suitable lead time, in order to be able to issue appropriate warnings and take appropriate emergency actions. Recent improvements in both flood plain characterization and computational capabilities have made the use of distributed...

The Data-Based Mechanistic (DBM) modelling philosophy emphasises the importance of parametrically efficient, low order, ‘dominant mode’ models, as well as the development of stochastic methods and the associated statistical analysis required for their identification and estimation....

The paper describes a general approach to the modelling of nonlinear and nonstationary economic systems from time-series data. This method exploits recursive state space filtering and fixed interval smoothing algorithms to decompose the time-series into long term trend and short term small...