Time-varying coefficient models with ARMA–GARCH structures for longitudinal data analysis
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Publication:5130149
DOI10.1080/02664763.2014.949638OpenAlexW1981739143MaRDI QIDQ5130149
Haiyan Zhao, Xu-Feng Niu, Fred W. Huffer
Publication date: 4 November 2020
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664763.2014.949638
Laplace approximationtime-varying coefficient modelsFramingham heart studyautoregressive conditional heteroscedasticity modelsautoregressive and moving-average models
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- Bayesian forecasting and dynamic models.
- Automatic approximation of the marginal likelihood in non-Gaussian hierarchical models
- A Bayesian analysis of the minimum AIC procedure
- Time series: theory and methods.
- Generalized autoregressive conditional heteroscedasticity
- Prediction in ARMA Models with GARCH in Mean Effects
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- A Bayesian extension of the minimum AIC procedure of autoregressive model fitting
- Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data
- Functional-Coefficient Autoregressive Models
- Estimation of the probability of an event as a function of several independent variables
- Analysis of Financial Time Series
- On Information and Sufficiency
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