this paper presents a simple yet powerful original approach for approximating dispersivity in porous media. the key to this approach is both use of least-squares criterion and image processing technique. two dimensional transparent models, including horizontal and vertical configurations, under different combinations of grain sizes and pore velocities, experimented. concentration data were obta...

recently, in order to increase the efficiency of least squares method in numerical solution of ill-posed problems, the chain least squares method is presented in a recurrent process by babolian et al. despite the fact that the given method has many advantages in terms of accuracy and stability, it does not have any stopping criterion and has high computational cost. in this article, the attempt...

In this article, a new approach to tidal harmonic analysis is introduced. This approach incorporates more constituents in the least squares method for a fixed duration of noise-free tidal record and results in a more accurate tidal prediction. Moreover, it is demonstrated that 135 days of hourly data, which is significantly less than 369 days data in the Rayleigh criterion, is sufficient for th...

Monotone single index models have gained over the past decades increasing popularity due to their flexibility and versatile use in diverse areas. Semi-parametric estimators such as least squares maximum likelihood of unknown monotone ridge function were considered make inference without having choose some tuning parameter. Description asymptotic behavior those crucially depends on acquiring a g...

For the purpose of exploring and modelling the relationships between a dataset and several datasets, multiblock Partial Least Squares is a widely-used regression technique. It is designed as an extension of PLS which aims at linking two datasets. In the same vein, we propose an extension of Redundancy Analysis to the multiblock setting. We show that PLS and multiblock Redundancy Analysis aim at...

A bias-correction method for closed-loop identi"cation, introduced in the literature as the bias-eliminated least-squares (BELS) method (Zheng & Feng, Automatica 31 (1995) 1019), is shown to be equivalent to a basic instrumental variable estimator applied to a predictor for the closed-loop system. This predictor is a function of the plant parameters and the known controller. Corresponding to th...

It is shown that, in comparison to the results obtained from a conventional least squares approach, a total least squares solution leads to significant improvements in the geometry and appearance of images synthesised in a linear combination of views procedure. Use of the total least squares criterion is appropriate when errors on the control points are independently and identically distributed...

Many industrial experiments involve restricted rather than complete randomization. This often leads to the use of split-plot designs, which limit the number of independent settings of some of the experimental factors. These factors, named whole-plot factors, are often, in some way, hard to change. The remaining factors, called sub-plot factors, are easier to change. Their levels are therefore i...

This paper deals with the problem of multivariate affine regression in the presence of outliers in the data. The method discussed is based on weighted orthogonal least squares. The weights associated with the data satisfy a suitable optimality criterion and are computed by a two-step algorithm requiring a RANSAC step and a gradient-based optimization step. Issues related to the breakdown point ...