Bootstrapping periodically autoregressive models
Copyright policy )Bootstrapping periodically autoregressive models
The main objective of this paper is to establish the residual and the wild bootstrap procedures for periodically autoregressive models. We use the least squares estimators of model’s parameters and generate their bootstrap equivalents. We prove that the bootstrap procedures for causal periodic autoregressive time series with finite fourth moments are weakly consistent. Finally, we confirm our theoretical considerations by simulations.
Time series, auto-correlation, regression, etc. in statistics (GARCH), least squares estimation, Bootstrap, jackknife and other resampling methods, periodically autoregressive models, [MATH] Mathematics [math], time series, bootstrap, Bootstrap, Asymptotic properties of parametric estimators
Time series, auto-correlation, regression, etc. in statistics (GARCH), least squares estimation, Bootstrap, jackknife and other resampling methods, periodically autoregressive models, [MATH] Mathematics [math], time series, bootstrap, Bootstrap, Asymptotic properties of parametric estimators
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