Análise bayesiana de sensibilidade do modelo AR(1) para dados em painel: uma aplicação em dados temporais de microarrays

Abstract

We considered a Bayesian analysis of first order autoregressive, AR(1), panel data model, using exact likelihood function, comparative analysis of prior distributions (sensitivity analysis) and predictive distributions of future observations. The methodology efficiency was evaluated by a simulation study using three prior, which were related to different Generalized Beta distributions: symmetric, asymmetric and uniform prior. We applied the proposed methodology to microarray time series real data of HeLa cells. The forecast of gene expression in one future time showed high efficiency.