Frequency domain minimum distance inference for possibly noninvertible and noncausal ARMA models

DOI10.1214/17-AOS1560zbMath1401.62178OpenAlexW2795477385MaRDI QIDQ1750279

Ignacio N. Lobato, Carlos Velasco

Publication date: 18 May 2018

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/17-aos1560

zbMATH Keywords

higher-order spectrahigher-order momentsautoregressive moving average modelnonminimum phaseWhittle estimateminimum distance inference

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (7)

Efficient GMM estimation with singular system of moment conditions ⋮ Specification testing with estimated variables ⋮ Identification and Estimation of Structural VARMA Models Using Higher Order Dynamics ⋮ Generalized Covariance Estimator ⋮ Frequency domain minimum distance inference for possibly noninvertible and noncausal ARMA models ⋮ Efficiency improvements for minimum distance estimation of causal and invertible ARMA models ⋮ Estimation of time series models using residuals dependence measures

Cites Work

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• Bilinear stochastic models and related problems of nonlinear time series analysis. A frequency domain approach
• Frequency domain minimum distance inference for possibly noninvertible and noncausal ARMA models
• Least absolute deviation estimation for all-pass time series models
• Quasi-likelihood Estimation of Non-invertible Moving Average Processes
• Fiscal Foresight and Information Flows
• Noncausal Autoregressions for Economic Time Series
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