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Bayesian Inference For State Space Model With Panel Data

Ranjita Pandey () and Anoop Chaturvedi ()

Statistics in Transition new series, 2016, vol. 17, issue 2, 211-219

Abstract: The present work explores panel data set-up in a Bayesian state space model. The conditional posterior densities of parameters are utilized to determine the marginal posterior densities using the Gibbs sampler. An efficient one step ahead predictive density mechanism is developed to further the state of art in prediction-based decision making.

Keywords: Bayesian analysis; Gibbs sampler; conditional posterior densities; predictive distribution (search for similar items in EconPapers)
Date: 2016
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Journal Article: BAYESIAN INFERENCE FOR STATE SPACE MODEL WITH PANEL DATA (2016) Downloads
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