The objectives of this study were to assess the genotype (G) by environment (E) interaction of grain yield of durum wheat(Triticum durum Desf.) based on parametric models, additive main effects and multiplicative interaction (AMMI) and joint linear regression models; and compare the relative efficiency of the two models in explaining the GE effects. Twenty-three genotypes were evaluated across ...

In this study a new two-parameter estimator which includes the ordinary least squares (OLS), the principal components regression (PCR) and the Liu-type estimator is proposed. Conditions for the superiority of this new estimator over the PCR, r-k class estimator and Liu-type estimator are derived. Furthermore the performance of this estimator is compared with the other estimators in different co...

The prevalence of obesity has increased dramatically in recent decades. It is an important public health issue as it causes many other chronic health conditions, such as hypertension, cardiovascular diseases, and type II diabetics. Obesity affects life expectancy and even the quality of lives. Eventually, it increases social costs in many ways due to increasing costs of health care and workplac...

CCondnue on reverse side If necessary and identity by block number) Analysis on a regional basis of the NORSAR seismic bulletin data for the three years from April 1972 to March 1975 shows that there has been no significant tf^"/^^J?^^ detectability during this time period. The detectability has been examined using" the least squares ^\^^' ^! least squares incremental method and the °-^h^ e men...

We study a class of models in which the law of motion perceived by agents influences the law of motion that they actually face. We assume that agents update their perceived law of motion by least squares. We show how the perceived law of motion and the actual one may converge to one another, depending on the behavior of a particular ordinary differential equation. The differential equation invo...

This article deals with estimation of the change-point in a sequence of independent random variables. It is based on a least squares process endowed with a weight function. For finite sample sizes we derive bounds of the error probability. They immediately yield rates of consistency which are known to be optimal. Our findings extend and sharpen earlier results of Antoch, Hušková and Veraverbeke...

In the presence of outliers in a dataset, a least squares estimation may not be the most adequate choice to get representative results. Indeed estimations could have been excessively influenced even by a very limited number of atypical observations. In this article, we propose a new Hausman-type test to check for this. The test is based on the trade-off between robustness and efficiency and all...

This is a more serious departure from the assumptions of the classical linear model than was the case for the Generalized Regression model, which maintained E("jX) = 0 but permitted nonconstant variances and/or nonzero correlations across error terms. Unlike the Generalized Regression model, the classical least squares estimator will be inconsistent for if the errors are correlated with the reg...

We consider estimation of linear functionals of the error distribution for two regression models: parametric and nonparametric, and for two types of errors: independent of the covariate and centered (type I), and conditionally centered given the covariate (type II). We show that the residual-based empirical estimators for the nonparametric type I model remain efficient in the type II model. For...