Bivariate and Multivariate Data Cloning through Non Linear Regression Models

Sajid Hussain, Zafar Iqbal, None Muhammad Mansoor, None Rashid Ahmed
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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.
利用非线性回归模型克隆双变量和多变量数据
非线性回归分析在数学、工程和社会科学领域具有重要的普及意义。金融学、生物学和自然化学等学科已经广泛地使用了非线性回归模型(nlrm)。克隆数据集在这些领域有其自身的重要性,它为实际数据集提供了二元和多元非线性回归模型的相同拟合。这篇文章提出了一个序列的克隆数据集,给出完全相同的拟合的二元和多元非线性回归模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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