Semiparametric Time Series Models with Log‐concave Innovations: Maximum Likelihood Estimation and its Consistency
DOI10.1111/sjos.12092zbMath1378.62061arXiv1111.6291OpenAlexW3123692285MaRDI QIDQ5177947
Publication date: 9 March 2015
Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1111.6291
consistencytime seriesmaximum likelihoodGARCHlog-concavityARMAsemiparametricshape constraintARMA-GARCH
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Statistics of extreme values; tail inference (62G32)
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- Semiparametric efficient adaptive estimation of asymmetric GARCH models
- Approximation by log-concave distributions, with applications to regression
- Maximum likelihood estimation of a log-concave density and its distribution function: basic properties and uniform consistency
- Quasi-concave density estimation
- Nonparametric estimation of multivariate convex-transformed densities
- Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE
- Independent component analysis via nonparametric maximum likelihood estimation
- Limit distribution theory for maximum likelihood estimation of a log-concave density
- On the estimation of a probability density function by the maximum penalized likelihood method
- Stationarity of GARCH processes and of some nonnegative time series
- Time series: theory and methods.
- Adaptive estimation in time-series models
- Optimal smoothing in adaptive location estimation
- Efficient estimation in semiparametric GARCH models
- On adaptive estimation in nonstationary ARMA models with GARCH errors
- Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
- On adaptive estimation in stationary ARMA processes
- Generalized autoregressive conditional heteroscedasticity
- Estimation of a convex function: Characterizations and asymptotic theory.
- Theoretical properties of the log-concave maximum likelihood estimator of a multidimensional density
- Log-concave probability and its applications
- Strictly stationary solutions of autoregressive moving average equations
- WEIGHTED LEAST ABSOLUTE DEVIATIONS ESTIMATION FOR ARMA MODELS WITH INFINITE VARIANCE
- Time series models with asymmetric Laplace innovations
- Multivariate log-concave distributions as a nearly parametric model
- ARMA MODELLING WITH NON-GAUSSIAN INNOVATIONS
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models
- Detecting the Presence of Mixing with Multiscale Maximum Likelihood
- Stochastic search for semiparametric linear regression models
- A Simplex Method for Function Minimization
- Optimal Transport
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