Modeling Bivariate Threshold Autoregressive Processes in the Presence of Missing Data

DOI10.1081/STA-200054435zbMath1073.62079MaRDI QIDQ4681056

Fabio H. Nieto

Publication date: 14 June 2005

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

zbMATH Keywords

nonlinear time seriesmissing dataTAR models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (8)

Penalized estimation of threshold auto-regressive models with many components and thresholds ⋮ Bayesian estimation of a multivariate TAR model when the noise process follows a Student-t distribution ⋮ Modeling and forecasting interval time series with threshold models ⋮ Using the Reversible Jump MCMC Procedure for Identifying and Estimating Univariate TAR Models ⋮ Forecasting with univariate TAR models ⋮ Unnamed Item ⋮ Bayesian analysis of multivariate threshold autoregressive models with missing data ⋮ Forecasting with Multivariate Threshold Autoregressive Models

Cites Work

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• Testing and Modeling Multivariate Threshold Models
• Testing and Modeling Threshold Autoregressive Processes
• On Tests for Self-Exciting Threshold Autoregressive-Type Non-Linearity in Partially Observed Time Series
• BAYESIAN INFERENCE OF THRESHOLD AUTOREGRESSIVE MODELS

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