کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5096155 1376507 2014 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Bayesian regression with heteroscedastic error density and parametric mean function
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آمار و احتمال
پیش نمایش صفحه اول مقاله
Bayesian regression with heteroscedastic error density and parametric mean function
چکیده انگلیسی
In this paper we consider Bayesian estimation of restricted conditional moment models with the linear regression as a particular example. A common practice in the Bayesian literature for linear regression and other semi-parametric models is to use flexible families of distributions for the errors and to assume that the errors are independent from covariates. However, a model with flexible covariate dependent error distributions should be preferred for the following reason. Assuming that the error distribution is independent of predictors might lead to inconsistent estimation of the parameters of interest when errors and covariates are dependent. To address this issue, we develop a Bayesian regression model with a parametric mean function defined by a conditional moment condition and flexible predictor dependent error densities. Sufficient conditions to achieve posterior consistency of the regression parameters and conditional error densities are provided. In experiments, the proposed method compares favorably with classical and alternative Bayesian estimation methods for the estimation of the regression coefficients and conditional densities.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 178, Part 3, January 2014, Pages 624-638
نویسندگان
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