Detecting and modelling serial dependence in non-Gaussian and nonlinear time series. (Abstract of thesis). (English) Zbl 1378.62071
From the text: Discrete time series data is seen in a wide variety of disciplines including biology, medicine, psychology, criminology and economics. However, traditional methods of detecting serial correlation in time series are not specifically designed for detecting serial dependence in discrete-valued time series. Thus new methods are needed to provide informative and implementable testing approaches.
MSC:
62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
62F12 | Asymptotic properties of parametric estimators |
62G08 | Nonparametric regression and quantile regression |
62J12 | Generalized linear models (logistic models) |