Bootstrapping periodically autoregressive models

Ciołek, Gabriela; Potorski, Paweł

ESAIM: Probability and Statistics, Tome 21 (2017), pp. 394-411.

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.

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