We consider Bayesian estimation of restricted conditional moment models with linear regression as a particular example …. -- Bayesian semiparametrics ; Bayesian conditional density estimation ; heteroscedastic linear regression ; posterior consistency …

Central limit theorems are developed for instrumental variables estimates of linear and semiparametric partly linear … regression models for spatial data. General forms of spatial dependence and heterogeneity in explanatory variables and …

linear regression (namely IMLR) model and support vector regression with particle swarm optimization algorithm (namely SVR …

such as multiple linear regression, linear discriminant analysis, artificial neural network and decision tree. They used 14 …

method based on linear regression analysis to characterize the relationship between different quality factors and the … the effects of various quality factors on that sample. The weights assigned to the different quality factors by the linear … regression model reflect the impact of those quality factors on the performance of the recognition system. Therefore, the …

linear regression. Analyzing consumers' perception of healthy food products, in particular, organic and functional foods, is …

using a linear regression approach. The predictor assumes three affective states in which a user can be: positive, negative …