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http://dx.doi.org/10.5351/KJAS.2005.18.1.043

L-Estimation for the Parameter of the AR(l) Model  

Han Sang Moon (Dept. of Statistics, University of Seoul)
Jung Byoung Cheal (Dept. of Statistics, Sungshin University)
Publication Information
The Korean Journal of Applied Statistics / v.18, no.1, 2005 , pp. 43-56 More about this Journal
Abstract
In this study, a robust estimation method for the first-order autocorrelation coefficient in the time series model following AR(l) process with additive outlier(AO) is investigated. We propose the L-type trimmed least squares estimation method using the preliminary estimator (PE) suggested by Rupport and Carroll (1980) in multiple regression model. In addition, using Mallows' weight function in order to down-weight the outlier of X-axis, the bounded-influence PE (BIPE) estimator is obtained and the mean squared error (MSE) performance of various estimators for autocorrelation coefficient are compared using Monte Carlo experiments. From the results of Monte-Carlo study, the efficiency of BIPE(LAD) estimator using the generalized-LAD to preliminary estimator performs well relative to other estimators.
Keywords
AR(l); Parameter; L-estimation;
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