A likelihood based estimator for vector autoregressive processes

DOI10.1016/j.stamet.2008.11.002zbMath1463.62252OpenAlexW1978214120MaRDI QIDQ537365

Wayne A. Fuller, Anindya Roy, Yan Yan Zhou

Publication date: 20 May 2011

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2008.11.002

zbMATH Keywords

Yule-Walker estimatorvector autoregressive processunconditional maximum likelihood

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Non-Markovian processes: estimation (62M09)

Related Items (1)

Maximum likelihood parameter estimation algorithm for controlled autoregressive autoregressive models

Cites Work

• Unnamed Item
• Gaussian likelihood estimation for nearly nonstationary AR(1) processes
• Asymptotic properties of multivariate nonstationary processes with applications to autoregressions
• The asymptotic distribution of the likelihood ratio for autoregressive time series with a regression trend
• Statistical analysis of cointegration vectors
• Testing for a unit root nonstationarity in multivariate autoregressive time series
• Adaptive estimation in time-series models
• On adaptive estimation in stationary ARMA processes
• Estimation for Partially Nonstationary Multivariate Autoregressive Models
• Multiple Time Series Regression with Integrated Processes
• A Unified Approach to Identifying Multivariate Time Series Models
• Fully Modified Least Squares and Vector Autoregression
• Efficient Tests for an Autoregressive Unit Root
• Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models

This page was built for publication: A likelihood based estimator for vector autoregressive processes