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http://dx.doi.org/10.5351/KJAS.2019.32.1.099

Robust confidence interval for random coefficient autoregressive model with bootstrap method  

Jo, Na Rae (Department of Information and Statistics, Chungbuk National University)
Lim, Do Sang (Division of Chronic Disease Control Prevention, Korea Centers for Disease Control & Prevention)
Lee, Sung Duck (Department of Information and Statistics, Chungbuk National University)
Publication Information
The Korean Journal of Applied Statistics / v.32, no.1, 2019 , pp. 99-109 More about this Journal
Abstract
We compared the confidence intervals of estimators using various bootstrap methods for a Random Coefficient Autoregressive(RCA) model. We consider a Quasi score estimator and M-Quasi score estimator using Huber, Tukey, Andrew and Hempel functions as bounded functions, that do not have required assumption of distribution. A standard bootstrap method, percentile bootstrap method, studentized bootstrap method and hybrid bootstrap method were proposed for the estimations, respectively. In a simulation study, we compared the asymptotic confidence intervals of the Quasi score and M-Quasi score estimator with the bootstrap confidence intervals using the four bootstrap methods when the underlying distribution of the error term of the RCA model follows the normal distribution, the contaminated normal distribution and the double exponential distribution, respectively.
Keywords
random coefficient autoregressive model; standard bootstrap method; percentile bootstrap method; studentized bootstrap method; hybrid bootstrap method;
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Times Cited By KSCI : 2  (Citation Analysis)
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