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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.
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