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BOOTSTRAPPING STATIONARY AUTOREGRESSIVE MOVING‐AVERAGE MODELS

机译:BOOTSTRAPPING STATIONARY AUTOREGRESSIVE MOVING‐AVERAGE MODELS

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Abstract.In this paper we develop an asymptotic theory for application of the bootstrap to stationary stochastic processes of autoregressive moving‐average (ARMA) type, with known order (p, q). We give a proof of the asymptotic validity of the bootstrap proposal applied to M estimators for the unknown parameter vector of the process. For this purpose we derive an asymptotic expansion for M estimators in ARMA models and construct an estimate for the unknown distribution function of the residuals which in principle are not observable. A small simulation study is also include

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