한국통계학회:학술대회논문집 (Proceedings of the Korean Statistical Society Conference)
- 한국통계학회 2003년도 춘계 학술발표회 논문집
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- Pages.183-189
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- 2003
BAYESIAN INFERENCE FOR MTAR MODEL WITH INCOMPLETE DATA
- Park, Soo-Jung (Department of Statistics, Ewha Womans University) ;
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Oh, Man-Suk
(Department of Statistics, Ewha Womans University)
;
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Shin, Dong-Wan
(Department of Statistics, Ewha Womans University)
- 발행 : 2003.05.23
초록
A momentum threshold autoregressive (MTAR) model, a nonlinear autoregressive model, is analyzed in a Bayesian framework. Parameter estimation in the presence of missing data is done by using Markov chain Monte Carlo methods. We also propose simple Bayesian test procedures for asymmetry and unit roots. The proposed method is applied to a set of Korea unemployment rate data and reveals evidence for asymmetry and a unit root.