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...

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...

Developed in [Deng and Lin, 2014], Least-Squares Progressive Iterative Approximation (LSPIA) is an efficient iterative method for solving B-spline curve and surface least-squares fitting systems. In [Deng and Lin 2014], it was shown that LSPIA is convergent when the iterative matrix is nonsingular. In this paper, we will show that LSPIA is still convergent even the iterative matrix is singular.

We present a new implementation of the commonly used Box-fitting Least Squares (BLS) algorithm, for detection transiting exoplanets in photometric data. Unlike BLS, our - Sparse BLS (SBLS), does not use binning data into phase bins, nor it any kind grid. Thus, its efficiency depend on transit phase, and is therefore slightly better than that BLS. For sparse data, also significantly faster It pe...

Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems C. A. Cantrell National Center for Atmospheric Research, Atmospheric Chemistry Division, 1850 Table Mesa Drive, Boulder, CO 80305, USA Received: 13 February 2008 – Accepted: 21 February 2008 – Published: 1 April 2008 Correspondence to: C. A. Cantrell ([email protected]) P...

Least-squares fitting, first developed by Carl Friedrich Gauss, is arguably the most widely used technique in statistical data analysis. It provides a method through which the parameters of a model can be optimised in order to obtain the best fit to a data set through the minimisation of the squared differences between the model and the data. This tutorial document describes the closely associa...