Forecasting with serially correlated regression models
DOI10.1080/00949650310001620112zbMath1052.62091OpenAlexW2030634867MaRDI QIDQ4826352
Publication date: 11 November 2004
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949650310001620112
simulationsgeneralized least squaresARMA processesasymptotic mean squared errorsautoregressive disturbancesincorrect generalized least squarespredictive mean squared efficiency
Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Statistical tables (62Q05)
Related Items (2)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Estimation of a linear regression model with stationary ARMA (p,q) errors
- Useful invariance results for generalized regression models
- Consistent autoregressive spectral estimates
- Linear prediction by autoregressive model fitting in the time domain
- Generalized Least Squares with Misspecified Serial Correlation Structures
- On the Prediction Efficiency of the Generalized Least Squares Model with an Estimated Variance Covariance Matrix
- Generalized Least Squares with an Estimated Autocovariance Matrix
- The Asymptotic Mean Squared Error of Multistep Prediction from the Regression Model with Autoregressive Errors
- Specification of the Disturbance for Efficient Estimation
- Best Linear Unbiased Prediction in the Generalized Linear Regression Model
- Least squares estimation in the regression model with autoregressive-moving average errors
- Application of Least Squares Regression to Relationships Containing Auto- Correlated Error Terms
This page was built for publication: Forecasting with serially correlated regression models
