Gender Wage-Productivity Differentials and Global Integration in China In the absence of discrimination, there should be no wage-productivity differentials as relative wages should be equal to the relative marginal productivity levels of workers. This paper investigates the role of globalization on the structure and evolution of gender differentials in China by simultaneously estimating demand-...

This paper deals with the design and identification of the dynamic model of a compactor, an articulated frame steering mobile engine for use in road construction. A classical approach based on an Ordinary Least Squares identification method is used. A survey of these techniques is given and applied to estimate dynamic parameters of the compactor, and especially the contribution of the contact s...

Abbreviations 3D D three-dimensional; C D molar concentration of a drug; CBG D corticosteroid binding globulin; CoMFA D comparative molecular field analysis; CoMSIA D comparative molecular similarity indices analysis; GOLPE D generating optimal linear PLS estimations; PLS D partial least squares; PRESS D predictive residual sum of squares; RMS D root mean squares; TBG D testosterone binding glo...

After diagnose the model and something was detected, there needs an adjustment for model fitting. For example, if non-equal variance happens, either use the transformation of response or other choices. If there are influential points in the dataset, we may try to avoid its influence by different fitting method (Robust Methods). If the relation between response and predictors are absolute not li...

Summary: We consider the problem of estimating the first k coefficients in a regression equation with k + 1 variables. For this problem with known variance of innovations, the neutral Laplace weighted-average least-squares estimator was introduced in Magnus (2002). We investigate properties of this estimator in the case where the unknown variance is estimated by least squares. We find that the ...

In this paper we study the estimator of the Partially linear Varying-coefficient Errors-inVariable model with stochastic linear restrictions. We present a mixed Profile least squares estimator when the covariates in the linear part are measured with additive error and some additional stochastic linear restrictions on the parametric component are available.

In this note a local thinning of the data locations is proposed, in order to construct a least squares multiquadric approximant stable and close to the multiquadric interpolant

vii List of Figures x List of Tables xi I Direct Minimization of the Equation Residuals 1