This paper considers model averaging as a way to select instruments for the two stage least squares and limited information maximum likelihood estimators in the presence of many instruments. We propose averaging across least squares predictions of the endogenous variables obtained from many different choices of instruments and then use the average predicted value of the endogenous variables in ...

Boundary integral equations (BIE) are reformulations of boundary value problems for partial differential equations. There is a plethora of research on numerical methods for all types of these equations such as solving by discretization which includes numerical integration. In this paper, the Neumann problem is reformulated to a BIE, and then moving least squares as a meshless method is describe...

A new numerical model of the lattice Boltzmann method utilizing least-squares finite element in space and Crank-Nicolson method in time is presented. The new method is able to solve problem domains that contain complex or irregular geometric boundaries by using finite-element method's geometric flexibility and numerical stability, while employing efficient and accurate least-squares optimizatio...

In the machine learning field, feature selection is used to discard the redundant information and improve the learning accuracy. In this paper, the redundant information is reused in the learning of partial least squares method within the frame of multitask learning. This newly proposed method is used to solve the multivariate calibration problem, a classic problem in the analytical chemistry f...

To my beloved wife, Yuijn iii ACKNOWLEDGEMENTS First, I want to thank my wife Yujin for her enduring patience and loving support during my study. She has been always there for me from the very beginning to this very end. She has been at the core of my motivation even when I was doubting if could finish this program. I also have to mention my beloved children, Lynn and Olivia, who have been an e...

In applying the level-set method developed in [Van den Berg and Friedlander, SIAM J. on Scientific Computing, 31 (2008), pp. 890–912 and SIAM J. on Optimization, 21 (2011), pp. 1201– 1229] to solve the fused lasso problems, one needs to solve a sequence of regularized least squares subproblems. In order to make the level-set method practical, we develop a highly efficient inexact semismooth New...

This paper describes various time-domain methods useful for analyzing the experimental data obtained from a circular cylinder force in terms of both wave and current for estimation of the drag and inertia coefficients applicable to the Morison’s equation. An additional approach, weighted least squares method is also introduced. A set of data obtained from experiments on heavily roughened circul...

The lossless compression of electroencephalographic (EEG) data is of great interest to the biomedical research community. In this paper, a two-stage technique of lossless compression involving decorrelating the sample points of the EEG signal and then entropy coding the resulting signal is examined. Two alternatives are presented for performing the rst task. Speciically, the rst stage consists ...