bayesian inference in stochastic form of multiplicative error model

In this paper, a stochastic form of multiplicative error model is presentedby considering the long term trend as the process of a state space model. optimalfiltering technique via sequential monte carlo perspective is developed for trackingthe long term trend as the hidden state of this model and the bayesian frameworkis applied to the estimation of both the hidden state and the unknown parametersusing particle marginal metropolis hastings scheme. a real world application is alsoperformed to illustrate and evaluate the proposed methodology.