Bivariate and Multivariate Data Cloning through Non Linear Regression Models

Sajid Hussain; Zafar Iqbal; Muhammad Mansoor; Rashid Ahmed

doi:10.32350/sir.73.01

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Bivariate and Multivariate Data Cloning through Non Linear Regression Models

Author(s)

Sajid Hussain Department of Statistics, The Islamia University of Bahawalpur, Pakistan

Zafar Iqbal Department of Statistics, The Islamia University of Bahawalpur, Pakistan

Muhammad Mansoor Department of Statistics, Government S. E. College, Bahawalpur, Pakistan

Rashid Ahmed Department of Statistics, The Islamia University of Bahawalpur, Pakistan

Abstract

Nonlinear regression analysis holds significant popularity in mathematical, engineering, and social science domains. Disciplines like financial matters, biology, and natural chemistry have broadly utilized nonlinear regression models (NLRMs). Cloned datasets have their own importance in such areas which provide the same fit of bivariate and multivariate nonlinear regression models for the actual datasets. This article presents a sequence of cloned datasets that give exactly the same fit of bivariate and multivariate nonlinear regression models

Publication Details

Page(s) 1-21

DOI 10.32350/sir.73.01

Published Journal: Scientific Inquiry and Review, Volume: 7, Issue: 3, Year: 2023

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Keywords

Cloned Data, data visualization, nonlinear regression model, fictitious datasets