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A Note on Bootstrapping M-estimates from Unstable AR(2) Process with Infinite Variance Innovations

2016/03/08 by Sohrabi, Maryam, Zarepour, Mahmoud
#Applications (stat.AP) #FOS: Computer and information sciences #FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.1603.02665

Abstract

The limiting distribution for M-estimates in a non-stationary autoregressive model with heavy-tailed error is computationally intractable. To make inferences based on the M-estimates, the bootstrap procedure can be used to approximate the sampling distribution. In this paper, we show that the bootstrap scheme with m=o(n) resampling sample size when m/n → 0 is approximately valid in a multiple unit roots time series with innovations in the domain of attraction of a stable law with index 0

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