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Abstract: We propose a method to construct a proposal density for theMetropolis-Hastings algorithm in Markov Chain Monte Carlo MCMC simulations ofthe GARCH model. The proposal density is constructed adaptively by using thedata sampled by the MCMC metho d itself. It turns out that autocorrelationsbetween the data generated with our adaptive proposal density are greatlyreduced. Thus it is concluded that the adaptive construction method is veryefficient and works well for the MCMC simulations of the GARCH model.



Author: Tetsuya Takaishi

Source: https://arxiv.org/







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