Annex B: Sampling strategy
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چکیده
The basic idea of the proposed strategy is to use multiple chains sampled using the Metropolis Hasting algorithm (MH). The transition kernel we used for each chain is an isotropic Gaussian with small variance combined with a (randomly chosen) single parameter Gaussian proposal with same variance. The variance of the proposal kernel was determined based on early simulations in order to obtain an acceptable trade-off between exploration and rejection rate. Despite the asymptotic consistency of the algorithm, in our setting of interest, practical implementation of this algorithm has the following shortcoming:
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