A Sequential and Iterative Testing Procedure to Identify the Nature of a Time Series Generating Process

作者：Rusticelli Elena^*; Dagum Estela Bee

来源：Sequential Analysis, 2012, 31(2): 219-237.

DOI：10.1080/07474946.2012.665721

• Conditional probability
• Inferential testing
• Nonlinear serial dependence
• Sequential and iterative procedure

An inferential approach is proposed to identify the nature of the generating process corresponding to a real time series. This new sequential and iterative testing procedure goes beyond the Box and Jenkins methodology for the identification, estimation, and validation of linear data generating processes by investigating the probabilistic structure of non-Gaussian estimated residuals {epsilon(t)} for the possible presence of nonlinear serial dependence. The testing procedure aims at indicating the right type of dependence present in a series by means of specific inferential tests on the moments of the generating structure probability distribution. The test statistics adopted are very popular and powerful and encompass a wide range of stochastic nonlinearity alternatives. The U.S. Industrial Production Index series is used to illustrate the iterative testing procedure proposed.

• 出版日期2012