Typically survey data have responses with gaps, outliers and ties, and the distributions of the responses might be skewed. Usually, in small area estimation, predictive inference is done using a two-stage Bayesian model with normality at both levels (responses and area means).This is the...

We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of the covariates. The model extends existing models in two important...

Typically survey data have responses with gaps, outliers and ties, and the distributions of the responses might be skewed. Usually, in small area estimation, predictive inference is done using a two-stage Bayesian model with normality at both levels (responses and area means).This is the...

We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the com- ponents changing smoothly as a function of the covariates. The model extends existing models in two...

Many economics and finance time series are non-Gaussian. In this paper, we propose a Bayesian approach to non-Gaussian autoregressive time series models via quantile functions. This approach is parametric, so we also compare the proposed parametric approach with a semi-parametric approach....

By utilizing the new Keynesian stochastic dynamic general equilibrium model, this paper examines the effects of credit easing policy on macroeconomic variables with or emphasizing on production. For this purpose, a model has been design including 5 sectors of household, enterprises, banks,...