Diagnostic Checking for Weibull Autoregressive Conditional Duration Models

DOI10.1007/978-1-4939-6568-7_4zbMath1367.62269OpenAlexW2560634268MaRDI QIDQ4976478

Guodong Li, Yang Li, Yao Zheng, Wai Keung Li

Publication date: 31 July 2017

Published in: Advances in Time Series Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-1-4939-6568-7_4

zbMATH Keywords

Weibull distributionresidual autocorrelationautoregressive conditional duration modelmodel diagnostic checking

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Economic time series analysis (91B84)

Cites Work

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• Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
• Generalized autoregressive conditional heteroscedasticity
• On the residual autocorrelation of the autoregressive conditional duration model
• DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED-RESIDUAL AUTOCORRELATIONS
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• On a measure of lack of fit in time series models
• ON THE SQUARED RESIDUAL AUTOCORRELATIONS IN NON-LINEAR TIME SERIES WITH CONDITIONAL HETEROSKEDASTICITY
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data

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