GRADING PARAMETERS OF A REGRESSION MODEL BASED ON SINGULAR VALUE DECOMPOSITION MATRICES

  • Атие Аднан Odessa National Polytechnic University
  • Георгий Николаевич Востров Odessa National Polytechnic University

Abstract

The problem of estimating the parameters of unconditional linear regression models in conditions of poor conditionality of the correlation matrix, quasimulticollinearity, cannot be precisely solved when using the classical least squares method (LSM). Developed a method for estimating the parameters of a regression model based on the LSM and the singular value decomposition of matrices of empirical data in case of quasimulticollinearity and poor conditionality of the correlation matrix

Author Biographies

Атие Аднан, Odessa National Polytechnic University
Graduate student
Георгий Николаевич Востров, Odessa National Polytechnic University

Cand. tech. sciences, associate professor

Published
2019-02-26
How to Cite
Аднан, А., & Востров, Г. (2019). GRADING PARAMETERS OF A REGRESSION MODEL BASED ON SINGULAR VALUE DECOMPOSITION MATRICES. Electrotechnic and Computer Systems, (11(87), 157-162. Retrieved from https://eltecs.op.edu.ua/index.php/journal/article/view/1471
Section
Dynamic Systems' Modelling