This paper develops a fast order-recursive square-root-free (SRF) QR-decomposition-based least-squares lattice (QRD-LSL) interpolation algorithm that significantly improves the numerical stability of ...

Soft-decision adaptive interpolation (SAI) provides a powerful framework for image interpolation. The robustness of SAI can be further improved by using weighted least-squares estimation, instead of ...

Least Squares Regression Line Linear regression is the process of modelling an association between two variables using a straight line, known as the regression line. When a regression line (not ...

Solutions employing least squares interpolation weights demonstrated non-monotonic behavior, leading to potential instability. In contrast, the use of dual-grid interpolation weights resulted in more ...

Whenever the command make clean is run, all .txt files will be deleted If you run the program multiple times with different input files (for example, first with . /parseTemps input/sample-input.txt ...

Welcome to pull requests! Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you ...

KEYWORDS: Numerical Partial Differential Equations, Boundary Value Problems, Radial Basis Function Methods, Ghost Points, Variable Shape Parameter, Least Squares JOURNAL NAME: Journal of Applied ...

Previously for DENSE, Lagrangian displacement estimation used two steps, including a first step of spatial interpolation or application of a spatial model (spatial interpolation with spatial ...

Pooled least squares Pooled least squares is a statistical method used in econometrics to estimate the parameters of a regression model by combining cross-sectional and time-series data into a ...

How do you calculate a least squares regression line by hand? When calculating least squares regressions by hand, the first step is to find the means of the dependent and independent variables. We do ...