A Portmanteau Test for Smooth Transition Autoregressive Models. (1st December 2019)

• Record Type: Journal Article
• Authors: Xia, Qiang; Zhang, Zhiqiang; Keung Li, Wai
• Is Part Of: Journal of time series analysis. Volume 41:Number 5(2020)
• Page Start: 722
• Page End: 730
• Publication Date: 2019-12-01
• Subjects: STAR models -- portmanteau test -- nonlinear time series -- least‐squares method; Time-series analysis -- Periodicals; 519.232
• DOI: 10.1111/jtsa.12512
• Languages: English
• ISSNs: 0143-9782

Abstract

Abstract : This article investigates a portmanteau test statistic for checking model adequacy of smooth transition autoregressive (STAR) models. The asymptotic distribution of residual autocorrelations and the least‐squares estimators are also derived. Hence, the correct asymptotic standard errors for residual autocorrelations are also obtained facilitating model diagnostic checking. Through the graphical display of the simulation results concerning the size and power, for commonly used nominal sizes ( ≤ 0 . 1 ), the portmanteau test appears to be more advantageous than the Lagrange multiplier tests in checking serial independence for the errors of STAR models.