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Bayesian Linear Regression with Conditional Heteroskedasticity

Yanyun Zhao

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: In this paper we consider adaptive Bayesian semiparametric analysis of the linear regression model in the presence of conditional heteroskedasticity. The distribution of the error term on predictors are modelled by a normal distribution with covariate-dependent variance. We show that a rate-adaptive procedure for all smoothness levels of this standard deviation function is performed if the prior is properly chosen. More specifically, we derive adaptive posterior distribution rate up to a logarithm factor for the conditional standard deviation based on a transformation of hierarchical Gaussian spline prior and log-spline prior respectively.

Keywords: Bayesian; linear; regression; Conditional; heteroskedasticity; Rate; of; convergence; Posterior; distribution; Adaptation; Hierarchical; Gaussian; spline; prior; Log-spline; prior (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2015-04-01
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