Generalized Least Squares for Trend Estimation of Summarized Dose–response Data

Generalized least squares-based parametric motion estimation

The estimation of parametric global motion had a significant attention during the last two decades, but despite the great efforts invested, there are still open issues. The most important ones are related to the accuracy of the estimation and to the ability to recover large deformation between images. In this paper, a new generalized least squares-based motion estimator is proposed. The non-lin...

Generalized Least Squares and Weigh- Ted Least Squares Estimation Methods for Distributional Parameters

• Regression procedures are often used for estimating distributional parameters because of their computational simplicity and useful graphical presentation. However, the resulting regression model may have heteroscedasticity and/or correction problems and thus, weighted least squares estimation or alternative estimation methods should be used. In this study, we consider generalized least square...

Weighted Least Squares Estimation with Missing Data

Generalized least squares estimation of panel with common shocks

This paper considers GLS estimation of linear panel models when the innovation and the regressors can both contain a factor structure. A novel feature of this approach is that preliminary estimation of the latent factor structure is not necessary. Under a set of regularity conditions here provided, we establish consistency and asymptotic normality of the feasible GLS estimator as both the cross...

Unifying Least Squares, Total Least Squares and Data Least Squares

The standard approaches to solving overdetermined linear systems Ax ≈ b construct minimal corrections to the vector b and/or the matrix A such that the corrected system is compatible. In ordinary least squares (LS) the correction is restricted to b, while in data least squares (DLS) it is restricted to A. In scaled total least squares (Scaled TLS) [15], corrections to both b and A are allowed, ...