Journal of Time Series Analysis · 2000 · 135 citations · 0 references
BusinessMathematicsEconometricsStatisticsTime Series AnalysisCointegration AnalysisMaximum Likelihood EstimationTime Series EconometricsTime Series ForecastingTime Series ModelingAutoregressive ModelsAutoregressive Time Series ModelsMaximum Likelihood InferenceRobust Time Series AnalysisRobust Time Series EstimationStatistical Time Series Models
We consider AR( q ) models in time series with non‐normal innovations represented by a member of a wide family of symmetric distributions (Student's t ). Since the ML (maximum likelihood) estimators are intractable, we derive the MML (modified maximum likelihood) estimators of the parameters and show that they are remarkably efficient. We use these estimators for hypothesis testing, and show that the resulting tests are robust and powerful.