Testing for a unit root in an arima(p,1,0) signal observed with ma(q) noise

DOI10.1080/03610929408831408zbMath0825.62230OpenAlexW1971777280MaRDI QIDQ4843674

No author found.

Publication date: 17 August 1995

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929408831408

zbMATH Keywords

maximum likelihood estimationMonte Carlo studymeasurement errorlarge samplerestricted ARIMA model

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

TESTING FOR A UNIT ROOT IN AN AR(1) TIME SERIES USING IRREGULARLY OBSERVED DATA ⋮ Maximum likelihood estimation for arma models in the presence of ARMA errors

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Time series: theory and methods
• Testing for unit roots in autoregressive moving average models. An instrumental variable approach
• Estimation of models of autoregressive signal plus white noise
• A central limit theorem for parameter estimation in stationary vector time series and its application to models for a signal observed with noise
• A note on testing for a unit root in an \(\text{ARIMA}(p,1,0)\) signal observed with \(\text{MA}(q)\) noise
• Consistent Estimates of Autoregressive Parameters and Extended Sample Autocorrelation Function for Stationary and Nonstationary ARMA Models
• Testing for unit roots in autoregressive-moving average models of unknown order
• Hypothesis Testing in ARIMA(p, 1, q) Models
• Testing for a unit root in time series regression
• Testing for a unit root in the presence of moving average errors
• Recursive parameter estimation of an autoregressive process disturbed by white noise
• MAXIMUM LIKELIHOOD ESTIMATION FOR AUTOREGRESSIVE PROCESSES DISTURBED BY A MOVING AVERAGE
• Estimation of the parameters of a time series subject to the error of rotation sampling
• Time Series Regression with a Unit Root
• Factorization of the Covariance Generating Function of a Pure Moving Average Process