Using a novel exploratory technique for time series analysis, Single Spectrum Analysis (SSA), it was possible to develop a comprehensive study of the Portuguese pharmaceutical market. The technique is described for the decomposition step, homogeneity structure testing and forecasting. A bibliography review was conducted on the technique. To the best of our knowledge, this was the first time that SSA was applied to any pharmaceutical market, so it was not possible to compare results with other published papers. An explanation on the Portuguese pharmaceutical market is provided in order to allow comprehensiveness of the work. The Portuguese pharmaceutical market is divided into 15 classes, which aggregates all drugs sold in the country. The technique was applied on the Total Market time series, which is the sum of those 15 time series. Applying SSA, time series were decomposed in the respective components, which can be described as trend, cyclical movements and seasonality. The structure of time series was tested for homogeneity. With those steps concluded, a monthly forecast for the years 2008 and 2009 (with the respective confidence bounds) was produced. As a complex methodology, decisions need to be taken in several steps of the study. Even if not all possible choices are presented in this article, lengthy analyses were done to reach the best possible results. In fact, choosing between possible window lengths, Singular Value Decomposition approaches, and eigentriples to be grouped together is sometimes more an art than a science; experience and previous knowledge of the actual phenomena can and should help. For confidentiality reasons the raw data are not provided in this article, but both forecast values and confidence bounds are presented.
- Pharmaceutical market
- Time series