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In this paper, we propose a new Metropolis Hasting (HS) Sampling known as the Local Metropolis Move for Machines Learning. The aim is to help support better implementation of the Markov Chain Monte Carlo (MCMC) Simulation for Bayesian Computation. The Variable Dimension SV model via the Changepoint Analysis was used to detect the accurate number of changepoint locations from the High Frequency Data (HFD) using the hourly Asian Foreign Exchange (FX) rates.We aim to use these for machine to detect changepoint location for identify the economic factors relevant to the country concerned during the crisis period. Our purpose is to examine whether the proposed MCMC algorithm can make machine think and capable to choose the appropriate number of changepoints for each systematic change of the problematic Asian Crisis currency in the Bayesian Inference via MCMC modeling.
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