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• W2185508738 abstract "Seasonal adjustment (SA) is an important method for the analysis of short term statistics. The two leading algorithms in that domain are Tramo-Seats (TS) and X12-Arima/X13-Arima-Seats (X12). Besides SA itself, the time series modelling features included in those programs are useful for numerous tasks like outliers' detection, forecasting or estimation of missing values. Taking into account the broad scope of those methods, we have developed a new set of object-oriented tools that can easily be plugged into in-house developments or that can be extended for new needs. The modules, which form JDemetra+, are completely written in Java and are available in open source form. In addition to the new implementations of TS and of X12, JDemetra+ has also been enriched to deal with related time series problems like structural models, non-standard SA methods, temporal disaggregation, benchmarking and business cycle analysis. All those problems are handled by means of a common state space framework, which can be used for other purposes. We will describe the architecture of JDemetra+ and we will give an overview of its main statistical features. Some of them will be illustrated by means of practical examples. The results provided by the original TS and X12 methods and by the new implementation will also be compared, using a set of real time series. Seasonal adjustment (SA) is an important step in the official statistics architecture. To achieve more harmonised practices, the SA Steering Group (a Eurostat-ECB group of experts) has encouraged the development of a flexible software solution for SA to be used within the European Statistical System. JDemetra+ is the last output of that initiative. The software, which is built on a set of object-oriented libraries developed at the National Bank of Belgium, includes new implementations of the two leading SA algorithms - TramoSeats (TS) and X12-Arima (X12), along with numerous tools for time series analysis. It is released as Open Source on the Joinup platform 1 . The need for statistical tools that can be integrated in an efficient way in various environments and that can be extended to face new requirements has been the driving force behind the developments. We shall give in the first parts of this paper a general overview of JDemetra+; we shall consider in more detail the SA framework of TS and X12 as well as the State space framework (SSF), which is hugely used in the current implementation. In the second part of the study, we shall focus on more practical aspects of the new software. Two small examples of use of the framework will be presented. In a last point, we shall shortly compare a specific aspect of the estimation procedures used in the original programs and in JDemetra+. 2. General overview of JDemetra+ JDemetra+ is essentially composed of two main blocks: the graphical interface and the underlying libraries, which can be used independently. The graphical interface - the only part that ordinary users interact with - is based on the NetBeans platform. By default, it gives a unified access to TS and to X12. Simplified interfaces to a few other SA methods (basic structural models...) are also provided, mainly for exploratory purposes. Third party IT teams can develop new modules that can be plugged into the original software in a transparent way. The other libraries are pure Java modules. They can be split into algorithmic packages - the core of the software, called - and peripheral services, like the access to external data providers or the formatting of the outputs. JTstoolkit provides low-level object-oriented services relating to common concepts of the time series domain, and more especially relating to the concepts handled in TS and in X12. Consequently, JDemetra+" @default.
• W2185508738 created "2016-06-24" @default.
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• W2185508738 date "2013-01-01" @default.
• W2185508738 modified "2023-09-26" @default.
• W2185508738 title "JDemetra+, an open framework for seasonal adjustment" @default.
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