A general model of regression using iterative series
Numerical Analysis
2021-03-26 v4 Numerical Analysis
Statistics Theory
Statistics Theory
Abstract
We present a new and general method of weighted least square univariate regression where the dependent variable is expanded as a series of suitably chosen functions of the independent variables. Each term of the series is obtained by an iterative process which reduces the sum of the square of the residuals. Thus by evaluating the regression series to a sufficiently large number of terms we can, in principle, reduce the sum of the square of residuals and improve the accuracy of the fit.
Cite
@article{arxiv.1110.0811,
title = {A general model of regression using iterative series},
author = {Nilotpal Kanti Sinha},
journal= {arXiv preprint arXiv:1110.0811},
year = {2021}
}
Comments
Need major changes and corrections