Diagnostic Checks in Time Series

Abstract

Diagnostic checking is an important step in the modeling process. But while the literature on diagnostic checks and time series modeling is quite extensive, it has been difficult to find a book that adequately covers methods for performing diagnostic checks." "Diagnostic Checks in Time Series helps to fill that gap. Author Wai Keung Li concentrates on diagnostic checks for stationary time series and covers a range of different linear and nonlinear models, from various ARMA, threshold type, and bilinear models to conditional non-Gaussian and autoregressive heteroscedasticity (ARCH) models. Because of its broad applicability, the portmanteau goodness-of-fit test receives particular attention, as does the score test. Unlike most treatments, the author's approach is a practical one, and he looks at each topic through the eyes of a model builder rather than a mathematical statistician.