A JOINT PORTMANTEAU TEST FOR CONDITIONAL MEAN AND VARIANCE TIME-SERIES MODELS
From MaRDI portal
Publication:2937712
DOI10.1111/jtsa.12091zbMath1311.62156OpenAlexW1515396033MaRDI QIDQ2937712
Publication date: 12 January 2015
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10016/20096
portmanteau statisticmodel diagnostic checkingestimation effectresidual serial correlationGARCH model specification testing
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: hypothesis testing (62M07) Diagnostics, and linear inference and regression (62J20)
Related Items
Diagnostic checking in FARIMA models with uncorrelated but non-independent error terms, Extremal Dependence-Based Specification Testing of Time Series, Generalized Covariance Estimator
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Joint and marginal specification tests for conditional mean and variance models
- Generalized autoregressive conditional heteroscedasticity
- Evaluating GARCH models.
- An Asymptotically Pivotal Transform of the Residuals Sample Autocorrelations With Application to Model Checking
- A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- A Class of Nonlinear Arch Models
- On a measure of lack of fit in time series models
- Autoregressive Conditional Density Estimation
- ON THE SQUARED RESIDUAL AUTOCORRELATIONS IN NON-LINEAR TIME SERIES WITH CONDITIONAL HETEROSKEDASTICITY
- TESTING FOR ZERO AUTOCORRELATION IN THE PRESENCE OF STATISTICAL DEPENDENCE
- Mixed Portmanteau Tests for Time‐Series Models
- Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models
- Correction to "An Extension of the Kolmogorov Distribution"
- Diagnostic Checking in ARMA Models With Uncorrelated Errors