Estimation in a class of nonlinear heteroscedastic time series models
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Publication:2426824
DOI10.1214/07-EJS157zbMath1135.62369arXiv0712.1673OpenAlexW3103296803MaRDI QIDQ2426824
Publication date: 14 May 2008
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0712.1673
Asymptotic properties of parametric estimators (62F12) Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)
Related Items
Density estimation for nonlinear parametric models with conditional heteroscedasticity, Variance bounds for estimators in autoregressive models with constraints, Conditional least squares estimation in nonstationary nonlinear stochastic regression models, Testing Symmetry of the Error Distribution in Nonlinear Heteroscedastic Models, QMLE of periodic bilinear models and of PARMA models with periodic bilinear innovations, A Cramér-von Mises test for symmetry of the error distribution in asymptotically stationary stochastic models, Estimating function approach for CHARN models, Testing nonstationary and absolutely regular nonlinear time series models
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Cites Work
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- AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
- Checking nonlinear heteroscedastic time series models
- Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach
- Estimation in nonlinear time series models
- Time series: theory and methods.
- Weak and strong uniform consistency of the kernel estimate of a density and its derivatives
- On conditional least squares estimation for stochastic processes
- On necessary and sufficient conditions for uniform strong consistency of estimators of a density and its derivatives
- Identification of nonlinear time series from first order cumulative characteristics
- The geometric ergodicity and existence of moments for a class of nonlinear time series model
- Quasi-likelihood and its application. A general approach to optimal parameter estimation
- Asymptotic theory of statistical inference for time series
- Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
- Generalized autoregressive conditional heteroscedasticity
- The efficiency of the estimators of the parameters in GARCH processes.
- Pseudo-maximum likelihood estimation of \(\text{ARCH}(\infty)\) models
- Quasi-maximum likelihood estimation in GARCH processes when some coefficients are equal to zero
- Least absolute deviations estimation for ARCH and GARCH models
- A crossvalidation method for estimating conditional densities
- Non-linear time series and Markov chains
- Estimation of conditional densities and sensitivity measures in nonlinear dynamical systems
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Parameter Estimation in Conditional Heteroscedastic Models
- Nonparametric Estimation and Symmetry Tests for Conditional Density Functions
- Weak convergence of some marked empirical processes: Application to testing heteroscedasticity
- WHITTLE ESTIMATION OF ARCH MODELS
- Consistency and Asymptotic Normality of the Quasi-Maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models
- Inference in Arch and Garch Models with Heavy-Tailed Errors
- A consistent test for conditional symmetry in time series models