Computing and estimating information matrices of weak ARMA models

DOI10.1016/j.csda.2011.07.006zbMath1239.62107OpenAlexW2028897467MaRDI QIDQ425392

Christian Francq, Michel Carbon, Yacouba Boubacar Maïnassara

Publication date: 8 June 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.07.006

zbMATH Keywords

nonlinear processesWald testLagrange multiplier testasymptotic relative efficiency (ARE)Bahadur slope

Mathematics Subject Classification ID

Related Items (12)

Temporal aggregation and systematic sampling for INGARCH processes ⋮ SCOMDY models based on pair-copula constructions with application to exchange rates ⋮ Modified Schwarz and Hannan-Quinn information criteria for weak VARMA models ⋮ On mixture autoregressive conditional heteroskedasticity ⋮ Goodness-of-fit tests for SPARMA models with dependent error terms ⋮ Estimating weak periodic vector autoregressive time series ⋮ Portmanteau tests for periodic ARMA models with dependent errors ⋮ Diagnostic checking in FARIMA models with uncorrelated but non-independent error terms ⋮ On the Fisher information matrix of a vector ARMA process ⋮ Estimation of the variance of the quasi-maximum likelihood estimator of weak VARMA models ⋮ Estimation of weak ARMA models with regime changes ⋮ Estimating FARIMA models with uncorrelated but non-independent error terms

Cites Work

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• Estimating linear representations of nonlinear processes
• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• HAC estimation and strong linearity testing in weak ARMA models
• Maximum likelihood estimation in nonlinear mixed effects models
• Efficient Monte Carlo computation of Fisher information matrix using prior information
• Basic properties of strong mixing conditions. A survey and some open questions
• Deriving the autocovariances of powers of Markov-switching GARCH models, with applications to statistical inference
• Time series: theory and methods.
• Consistent autoregressive spectral estimates
• Methods for recursive robust estimation of AR parameters
• Estimation of nonlinear time series with conditional heteroscedastic variances by iteratively weighted least squares
• The mixing property of bilinear and generalised random coefficient autoregressive models
• Least absolute deviation estimation for all-pass time series models
• Covariance matrix estimation for estimators of mixing weak ARMA models
• Estimation and information in stationary time series
• Bartlett's formula for a general class of nonlinear processes
• Inference For Autocorrelations Under Weak Assumptions
• EFFICIENT ESTIMATION OF PARAMETERS IN MOVING-AVERAGE MODELS
• On the Inversion of the Sample Covariance Matrix in a Stationary Autoregressive Process
• On the Evaluation of the Information Matrix for Multiplicative Seasonal Time-Series Models
• FISHER'S INFORMATION MATRIX FOR SEASONAL AUTOREGRESSIVE-MOVING AVERAGE MODELS
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• An algorithm for computing the asymptotic fisher information matrix for seasonal SISO models
• Testing the Nullity of GARCH Coefficients: Correction of the Standard Tests and Relative Efficiency Comparisons
• On the fitting of multivariate autoregressions, and the approximate canonical factorization of a spectral density matrix
• Linear‐representation Based Estimation of Stochastic Volatility Models
• Diagnostic Checking in ARMA Models With Uncorrelated Errors

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