Gaussian Maximum Likelihood Estimation For ARMA Models. I. Time Series
From MaRDI portal
Publication:3505309
DOI10.1111/j.1467-9892.2006.00492.xzbMath1141.62074OpenAlexW2063146705MaRDI QIDQ3505309
Publication date: 18 June 2008
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: http://eprints.lse.ac.uk/57580/
consistencyasymptotic normalitymartingale differenceGaussian maximum likelihood estimationARMA time series model
Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Stationary stochastic processes (60G10)
Related Items
Dirichlet ARMA models for compositional time series, Partitioning and interpolation based hybrid ARIMA-ANN model for time series forecasting, The asymptotic covariance matrix of the QMLE in ARMA models, Estimation of semivarying coefficient time series models with ARMA errors, A general result on the estimation bias of ARMA models, Gaussian maximum likelihood estimation for ARMA models. II: Spatial processes, Statistical inference for ARMA time series with moving average trend, Generalized ARMA models with martingale difference errors, Model selection for time series with nonlinear trend, On model Fitting and estimation of strictly stationary processes, Efficient likelihood estimation in state space models, Exact maximum likelihood estimation for non-stationary periodic time series models, A novel partial-linear single-index model for time series data, Tests for \(m\)-dependence based on sample splitting methods, Statistical inference for autoregressive models under heteroscedasticity of unknown form, Exact Likelihood Equations for Autoregression Models with Multivariate Elliptically Contoured Distributions, Consistency of global LSE for MA(1) models, Modified Gaussian likelihood estimators for ARMA models on \(\mathbb Z^d\), On strong consistency and asymptotic normality of one-step Gauss-Newton estimators in ARMA time series models, Estimating the mean and its effects on Neyman smooth tests of normality for ARMA models
Cites Work