The Use of Cone Projections and Quadratic programming in Estimation of Constrained Regression
Year: 2025
Type: article
Abstract: Statisticians often use regression models like parametric, nonparametric, and semi-parametric models to represent economic and social phenomena. These models explain the relationships between different variables in these phenomena. One of the parametric model techniques is conic projection regression. It helps to find the most important slopes for multidimensional data using prior information about the regression's parameters to estimate the most efficient estimator. R algorithms, written in the R language, simplify this complex method. These algorithms are based on quadratic programming, which makes the estimations more accurate.
Authors: Huda S. Ibrahim, Fadhaa M. Hashim
Institutions: University of Baghdad, Alrafidain University College
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410757011