The use of domain specific software frameworks can significantly speed up application development because they provide ready made components as well as a reusable design. This book presents the Java framework JStatCom which evolved from experiences made during the development of JMulTi, a popular software for time series analysis. It describes in detail the requirements for such a framework and offers solutions to all recurring tasks, for example, the internal data representation of complex statistical models, the interaction between the data model and the graphical user interface, and the management of computing tasks in a multithreaded environment. Furthermore, it is described how the process of interfacing external software packages for specific numerical calculations can be standardized. An abstract interface is presented that may be used to hide the underlying complexities of data type conversions and specific calling semantics from the user of the framework. The text comes with many code examples and UML diagrams that help to understand each subsystem. Developers planning to develop data analysis software in Java can greatly benefit from this book.

Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.

Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.