Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Note on Bootstrapping M-estimators in TAR Models

  • Kim, Sahmyeong (Department of Applied Statistics, Chung-Ang University)
  • Published : 2000.12.01
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Abstract

Kreiss and Franke(192) and Allen and Datta(1999) proposed bootstrapping the M-estimators in ARMA models. In this paper, we introduce the robust estimating function and investigate the bootstrap approximations of the M-estimators which are solutions of the estimating equations in TAR models. A number of simulation results are presented to estimate the sampling distribution of the M-estimators, and asymptotic validity of the bootstrap for the M-estimators is established.

Keywords

References

  1. Journal of Time Series Analysis v.20 A note on bootstrapping M-estimators in ARMA models Allen, M.;Datta, S.
  2. Biometrika v.72 Robust test for time series with an application to first-order autoregressive processes Basawa, I.V.;Huggins, R.M.;Staudte, R.G.
  3. Biometrika v.72 The foundations of finite sample estimation in stochastic processes Godambe, V.P.
  4. Inference for nonlinear time series models via estimating functions Kim, S.
  5. Journal of Time Series Analysis v.13 Bootstrapping stationary autoregressive moving average models Kreiss, J.P.;Franke, J.
  6. Journal of Applied Probability v.21 A threshold AR(1) model Petrucelli, J.D.;Woolford, S.W.