Parametric seemingly unrelated regression (SUR) models are a common tool for multivariate regression analysis when error variables are reasonably correlated, so that separate univariate analysis may result in inefficient estimates of covariate effects. A weakness of parametric models is that they require strong assumptions on the functional form of possibly nonlinear effects of metrical covaria...

Abstract Clusterwise regression is an approach to analysis based on finite mixtures which generally employed when sample observations come from a population composed of several unknown sub-populations. Whenever the response continuous, Gaussian clusterwise linear models are usually employed. Such have been recently robustified with respect possible presence mild outliers in However, some fields...

Nine additive allometric equations for computing above-ground, standing biomass were developed for the plant community and for each of 18 single species typical of the Tamaulipan thornscrub of north-eastern Mexico. Equations developed using additive procedures in seemingly unrelated linear regression provided statistical efficiency in total biomass estimates at the scales of both individual spe...

This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components. The approach treats the points on each nonparametric regression line as unknown parameters and uses a prior on the degree of smoothness of each line to ensure ...

abstract present study used translog cost function for determining break point of paddy farms. requested data set include inputs’ prices and quantities, and production amounts had been acquired from 500 rice farmers of guilan province at 2009. model used in this study is seemingly unrelated regressions (sur). the results showed that labor and pesticides had the highest and lowest share of produ...