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Finite sample properties of ml and reml estimators in time series regression models with long memory noise |
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| Abstract: | Finite sample properties of ML and REML estimators in time series regression models with fractional ARIMA noise are examined. In particular, theoretical approximations for bias of ML and REML estimators of the noise parameters are developed and their accuracy is assessed through simulations. The impact of noise parameter estimation on performance of t -statistics and likelihood ratio statistics for testing regression parameters is also investigated. |
| Keywords: | Bias Fractional Arima Model Maximum Likelihood Estimator Restricted Maximum Likelihood Estimator Root Mean Squared Error Time Series Regression Model |