We consider polynomial approximation on the unit sphere S² = {(x, y, z) Є R³ : x² + y² + z² = 1} by a class of regularized discrete least squares methods with novel choices for the regularization ...

Reduced rank approximation of matrices has hitherto been possible only by unweighted least squares. This paper presents iterative techniques for obtaining such approximations when weights are ...

The ARIMA procedure primarily uses the computational methods outlined by Box and Jenkins. Marquardt's method is used for the nonlinear least-squares iterations. Numerical approximations of the ...

The element‐free Galerkin (EFG) methods represent a significant progression in numerical analysis, harnessing meshless techniques to overcome challenges associated with conventional meshing. By ...

In this paper we present an algorithm to enhance the accuracy of the estimation of the parameters of linear stroke segments in a two-dimensional printed character image. The algorithm achieves high ...

Penalized least squares estimates provide a way to balance fitting the data closely and avoiding excessive roughness or rapid variation. A penalized least squares estimate is a surface that minimizes ...

In this talk we introduce an approach that augments least-squares finite element formulations with user-specified goals or quantities-of-interest. The method incorporates the quantity-of-interest into ...