- Volume 7 Issue 3
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.
- Journal of Time Series Analysis v.20 A note on bootstrapping M-estimators in ARMA models Allen, M.;Datta, S.
- 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.
- Biometrika v.72 The foundations of finite sample estimation in stochastic processes Godambe, V.P.
- Inference for nonlinear time series models via estimating functions Kim, S.
- Journal of Time Series Analysis v.13 Bootstrapping stationary autoregressive moving average models Kreiss, J.P.;Franke, J.
- Journal of Applied Probability v.21 A threshold AR(1) model Petrucelli, J.D.;Woolford, S.W.