T his study evaluates the causality relationship between human capital and foreign direct investment inflow in twenty-six OIC (the Organization of Islamic Cooperation) countries over the period 1970–2014. We employed the panel Granger non-causality testing approach of Kònya (2006) that is based on seemingly unrelated regression (SUR) systems, and Wald tests with country specific boot...

The aim of this study was to develop and evaluate models for predicting the carcass composition of lambs. Forty male lambs of two different breeds were included in our analysis. The lambs were slaughtered and their hot carcass weight was obtained. After cooling for 24 hours, the subcutaneous fat thickness was measured between the 12th and 13th rib and the total breast bone tissue thickness was ...

Seemingly unrelated regression (SUR) models traditionally appear in econometrics but recently also emerged in likelihood factorizations of Gaussian graphical models. The literature on maximum likelihood estimation in SUR seems not to mention the possibility of a multimodallikelihood. \eVe want to increase the awareness of this phenomenon by a thorough study of a two-equation model illustrated b...

We present a sparse seemingly unrelated regression (SSUR) model to generate substantively relevant structures in the high-dimensional distributions of seemingly unrelated model (SUR) parameters. This SSUR framework includes prior specifications, posterior computations using Markov chain Monte Carlo methods, evaluations of model uncertainty, and model structure searches. Extensions of the SSUR m...

Compared with other distribution functions, the Weibull distribution has been more widely used in describing diameter distributions because of its flexibility and relative simplicity. Parameters of the Weibull distribution are generally predicted either by the parameter prediction method or by the parameter recovery method. The coefficients of the regression equations for predicting Weibull par...

This paper considers the Ridge Feasible Generalized Least Squares Estimator (RFGLSE), Seemingly Unrelated Regression RSUR and proposes Kibria-Lukman KLSUR estimator for parameters of (SUR) model when regressors models are collinear. A simulation study was conducted to compare performance three different types estimators SUR model. Different correlation levels (0.0, 0.1, 0.2, ..., 0.9) among ind...

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...

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...