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In this paper, we propose a Bayesian methodology for
receiver function analysis, a key tool in determining the deep structure
of the Earth’s crust.We exploit the assumption of sparsity for
receiver functions to develop a Bayesian deconvolution
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适用于空间计量的各种模型,包括SVAR SEM SMD 等,以及各种检验,如LM Walds等-least-squares, simultaneous systems (2SLS,3SLS, SUR)
limited dependent variable (logit, probit, tobit) and Bayesian variants
time-series (VAR, BVAR, ECM) estimation and accompanying forecasting func
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