in this paper the meshless local petrov-galerkin (mlpg) method is implemented to study the buckling of isotropic cylindrical shells under axial load. displacement field equations, based on donnell and first order shear deformation theory, are taken into consideration. the set of governing equations of motion are numerically solved by the mlpg method in which according to a semi-inverse method, ...

We extend the results of De Luca et al. (2021) to inference for linear regression models based on weighted-average least squares (WALS), a frequentist model averaging approach with Bayesian flavor. We concentrate about single focus parameter, interpreted as causal effect policy or intervention, in presence potentially large number auxiliary parameters representing nuisance component model. In ...

For many least-squares decomposition models efficient algorithms are well known. A more difficult problem arises in decomposition models where each residual is weighted by a nonnegative value. A special case is principal components analysis with missing data. Kiers (1997) discusses an algorithm for minimizing weighted decomposition models by iterative majorization. In this paper, we propose a m...

This paper presents analysis of a weighted-norm least squares finite element method for elliptic problems with boundary singularities. We use H(div) conforming Raviart–Thomas elements and continuous piecewise polynomial elements. With only a rough estimate of the power of the singularity, we employ a simple, locally weighted L2 norm to eliminate the pollution effect and recover better rates of ...

oceanographic images obtained from environmental satellites by a wide range of sensors allow characterizing natural phenomena through different physical measurements. for instance sea surface temperature (sst) images, altimetry data and ocean color data can be used for characterizing currents and vortex structures in the ocean. the purpose of this thesis is to derive a relatively complete frame...

We consider two regularization approaches, the LASSO and the threshold-gradient-directed regularization, for estimation and variable selection in the accelerated failure time model with multiple covariates based on Stute's weighted least squares method. The Stute estimator uses Kaplan-Meier weights to account for censoring in the least squares criterion. The weighted least squares objective fun...