We present a new concept for image sequence processing that extends the classical brightness change constraint equation to incorporate changes due to dynamic physical processes. In order to estimate both the velocity and the parameters that govern the observed processes we introduce a general total least squares estimation framework. The strength of this technique is illustrated on a few exampl...

Using measured radial velocity data of nine double lined spectroscopic binary systems NSV 223, AB And, V2082 Cyg, HS Her, V918 Her, BV Dra, BW Dra, V2357 Oph, and YZ Cas, we find corresponding orbital and spectroscopic elements via the method introduced by Karami & Mohebi (2007a) and Karami & Teimoorinia (2007). Our numerical results are in good agreement with those obtained by others using mor...

Recent studies have used quantile regression (QR) techniques to estimate the impact of education on the location, scale and shape of the conditional wage distribution. We conduct a similar investigation of the role of work-related training. We utilise both ordinary least squares and QR techniques to estimate associations between work-related training and wages for private sector men in ten Euro...

We establish an a-posteriori error estimate, with corresponding bounds, that is valid for any FOSLS L-minimization problem. Such estimates follow almost immediately from the FOSLS formulation, but they are usually difficult to establish for other methodologies. We present some numerical examples to support our theoretical results. We also establish a local a-priori lower error bound that is use...

Using panel data, this paper tests whether foreign, public, and private capital have a positive and significant effect on aggregate output and labor productivity for Mexico during the 1960-2001 period. The richer information set made possible by the sectorial data enables this study to utilize the methodologically sound Agroup-mean@ Fully Modified Ordinary Least Squares (FMOLS) procedure develo...

Numerical tests are used to validate a practical estimate for the optimal backward errors of linear least squares problems. This solves a thirty-year-old problem suggested by Stewart and Wilkinson.

S U M M A R Y Least-squares linear regression is so popular that it is sometimes applied without checking whether its basic requirements are satisfied. In particular, in studying earthquake phenomena, the conditions (a) that the uncertainty on the independent variable is at least one order of magnitude smaller than the one on the dependent variable, (b) that both data and uncertainties are norm...

In this paper, the effect of misspecification due to omission of relevant variables on the dominance of the r −(k, d) class estimator proposed by Özkale (2012), over the ordinary least squares (OLS) estimator and some other competing estimators when some of the regressors in the linear regression model are correlated, have been studied with respect to the mean squared error criterion. A simulat...

This article surveys the history, development, and applications of least squares, including ordinary, constrained, weighted, and total least squares. The presentation includes proofs of the basic theory, in particular, unitary factorizations and singular-value decompositions of matrices. Numerical examples with real data demonstrate how to set up and solve several types of problems of least squ...

Levelling is the most precise technique for height difference measurements in geomatics engineering. Various systematic errors affect precise levelling observations and reduce the precision of the observed height differences. This study investigates digital levels residual compensator error and observational method for its elimination. For this purpose the levelling data, which was collected wi...