Diego J. Pedregal

Learn More
This paper describes in detail a flexible approach to nonstationary time series analysis based on a Dynamic Harmonic Regression (DHR) model of the Unobserved Components (UC) type, formulated with a stochastic state space setting. The model is particularly useful for adaptive seasonal adjustment, signal extraction and interpolation over gaps, as well as(More)
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 Extraction (OSE) theory, which is normally set in the frequency(More)
A new approach to time series modelling is used to explore how government spending and private capital investment may have influenced the unemployment rate in the USA between 1948 and 1988. The resulting model suggests strongly that the investigation of dynamic relationships between purely relative measures of the major macro-economic variables can help in(More)
The goal of this article is to evaluate the impact of the drastic Spanish Penal Code reform on the number of road deaths in Spain and the time that the effects might last. This is achieved by means of multivariate unobserved component models set up in a state space framework estimated using maximum likelihood. In short, with this reform Spain might be(More)
ii Captain Toolbox CAPTAIN is a MATLAB ® compatible toolbox for non stationary time series analysis, system identification, signal processing and forecasting, using unobserved components models, time variable parameter models, state dependent parameter models and multiple input transfer function models. CAPTAIN also includes functions for true digital(More)
Turnouts are probably the most important infrastructure elements of the railway system because of its effect on the system safety, reliability and quality of the service. In this paper, a predictive maintenance system in point mechanism, called RCM, has been implemented for increasing the quality service. RCM is based on the integration of the two other(More)
Sales forecasting is increasingly complex due to many factors, such as product life cycles that have become shorter, more competitive markets and aggressive marketing. Often, forecasts are produced using a Forecasting Support System that integrates univariate statistical forecasts with judgment from experts in the organization. Managers add information to(More)