Least-Squares Fitting of a Hyperplane

PEDOMODELS FITTING WITH FUZZY LEAST SQUARES REGRESSION

Pedomodels have become a popular topic in soil science and environmentalresearch. They are predictive functions of certain soil properties based on other easily orcheaply measured properties. The common method for fitting pedomodels is to use classicalregression analysis, based on the assumptions of data crispness and deterministic relationsamong variables. In modeling natural systems such as s...

l1-Regression based subdivision schemes for noisy data

Fitting curve and surface by least-regression is quite common inmany scientific fields. It, however cannot properly handle noisy data with impulsive noises and outliers. In this article, we study l1-regression and its associated reweighted least squares for data restoration. Unlike most existing work, we propose the l1-regression based subdivision schemes to handle this problem. In addition, we...

Determination of the best-fitting reference orbit for a LEO satellite using the Lagrange coefficients

Linearization of the nonlinear equations and iterative solution is the most well-known scheme in many engineering problems. For geodetic applications of the LEO satellites, e.g. the Earth’s gravity field recovery, one needs to provide an initial guess of the satellite location or the so-called reference orbit. Numerical integration can be utilized for generating the reference orbit if a satelli...

The least squares fit of a hyperplane to uncertain data

New Approach in Fitting Linear Regression Models with the Aim of Improving Accuracy and Power

The main contribution of this work lies in challenging the common practice of inferential statistics in the realm of simple linear regression for attaining a higher degree of accuracy when multiple observations are available, at least, at one level of the regressor variable. We derive sufficient conditions under which one can improve the accuracy of the interval estimations at quite affordable ...