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This paper describes a GAUSS program of a Markov-chain sampling algorithm for GARCH models proposed by Nakatsuma (1998). This algorithm allows us to generate Monte Carlo samples of parameters in a GARCH model from their joint posterior distribution. The samples obtained by this algorithm are...
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Three Bayesian methods (Markov chain Monte Carlo, Laplace approximation and quadrature formula) are developed to estimate the parameters of the ARMA-GARCH model. The ARMA-GARCH model is applied to weekly foreign exchange rate data of five major currencies, and their stochastic volatilities are...
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In this paper, we apply a Markov mixture model to capturing complex dynamics in the cross section distribution of per capita income across countries and examining the convergence hypothesis in economic growth. A Markov mixture model is estimated by a Bayesian procedure via the Gibbs sampler....
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