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http://dx.doi.org/10.5351/CSAM.2013.20.1.085

New Bootstrap Method for Autoregressive Models  

Hwang, Eunju (Institute of Mathematical Sciences and Department of Statistics, Ewha Womans University)
Shin, Dong Wan (Institute of Mathematical Sciences and Department of Statistics, Ewha Womans University)
Publication Information
Communications for Statistical Applications and Methods / v.20, no.1, 2013 , pp. 85-96 More about this Journal
Abstract
A new bootstrap method combined with the stationary bootstrap of Politis and Romano (1994) and the classical residual-based bootstrap is applied to stationary autoregressive (AR) time series models. A stationary bootstrap procedure is implemented for the ordinary least squares estimator (OLSE), along with classical bootstrap residuals for estimated errors, and its large sample validity is proved. A finite sample study numerically compares the proposed bootstrap estimator with the estimator based on the classical residual-based bootstrapping. The study shows that the proposed bootstrapping is more effective in estimating the AR coefficients than the residual-based bootstrapping.
Keywords
Autoregressive model; stationary bootstrap; residual-based bootstrap; asymptotic property;
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