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In this book, author Wai Keung Li--one of the world's top authorities in time series modeling--concentrates on diagnostic checking methods for stationary time series, bringing together the previously scattered literature on the subject. With clear explanations and a focus firmly on applications, he covers a range of different linear and nonlinear models, from various ARMA, and bilinear models to conditional non-Gaussian and ARCH models. Because of its broad applicability, the portmanteau goodness-of-fit test receives particular attention, as does the score test. Readers will understand the…mehr

Produktbeschreibung
In this book, author Wai Keung Li--one of the world's top authorities in time series modeling--concentrates on diagnostic checking methods for stationary time series, bringing together the previously scattered literature on the subject. With clear explanations and a focus firmly on applications, he covers a range of different linear and nonlinear models, from various ARMA, and bilinear models to conditional non-Gaussian and ARCH models. Because of its broad applicability, the portmanteau goodness-of-fit test receives particular attention, as does the score test. Readers will understand the relative merits of the models discussed, know how to estimate these models, and often find ways to improve a model.

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