Browse > Article
http://dx.doi.org/10.5351/CKSS.2006.13.3.745

Comparison of Bootstrap Methods for LAD Estimator in AR(1) Model  

Kang, Kee-Hoon (Department of Statistics, Hankuk University of Foreign Studies)
Shin, Key-Il (Department of Statistics, Hankuk University of Foreig Studies)
Publication Information
Communications for Statistical Applications and Methods / v.13, no.3, 2006 , pp. 745-754 More about this Journal
Abstract
It has been shown that LAD estimates are more efficient than LS estimates when the error distribution is double exponential in AR(1) model. In order to explore the performance of LAD estimates one can use bootstrap approaches. In this paper we consider the efficiencies of bootstrap methods when we apply LAD estimates with highly variable data. Monte Carlo simulation results are given for comparing generalized bootstrap, stationary bootstrap and threshold bootstrap methods.
Keywords
Least square estimator; stationary bootstrap; threshold bootstrap;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Li, H. and Maddala, G. (1996). Bootstrapping time series models. Econometric Theory, Vol. 15, 115-195
2 Shin, K-I., Kang, H.-J. and Sim, H. (2002). A new proof of efficient of LAD estimation in an autoregressive process. Journal of the Korean Statistical Society, Vol. 31, 121-128   과학기술학회마을
3 Park, D.S., Kim, Y.B., Shin, K.-I. and Willemain, T.R. (2001). Simulation output analysis using the threshold bootstrap. European journal of Operational Research, Vol. 134, 17-28   DOI   ScienceOn
4 Politis, D.N. and Romano, J.P. (1994). The stationary bootstrap. Journal of the American Statistical Association, Vol. 89, 1303-1313   DOI
5 HardIe, W., Horowitz, J. and Kreiss, J.P. (2003). Bootstrap methods for time series. International Statistical Review, Vol. 71, 435-460   DOI
6 Berkowitz, J. and Kilian, L. (2000). Recent developments in bootstrapping time series. Econometrics Reviews, Vol. 19, 1-48   DOI
7 Cao, R. (1999). An overview of bootstrap mothods for estimating and predicting in time series. Test, Vol. 8, 95-116   DOI
8 Efron, B and Tibshirani, R.J. (1993). An introduction to the Bootstrap, Chapman & Hall, New York
9 Kim, Y, Willemain, T., Haddock, J. and Runger, G. (1993). The threshold bootstrap: A new approach to simulation output analysis. In: Evans, G.W., Mollaghasemi, M., Russel, E.C., Biles, W.E. (Eds.) , Proceedings: 1993 Winter Simulation Conference, 498-502