What question did this study set out to answer?

August 1, 1976Biochemical JournalOpen Access

Methods for fitting equations with two or more non-linear parameters

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Authors

INI.A. NimmoEdinburgh Royal Infirmary GAGordon L. AtkinsLouisiana State University

Discussion

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Implication

Computational analysis demonstrates improved parameter accuracy across experimental datasets, suggesting simultaneous equation fitting outperforms sequential estimation.

Key Points

To evaluate mathematical approaches for fitting equations with two or more non-linear parameters to experimental data using least-squares criteria.
Assessed two mathematical fitting procedures: directly solving a system of non-linear simultaneous equations and applying Taylor's theorem.
Compared fitting non-linear equations to all experimental datasets simultaneously against fitting datasets sequentially one by one.
Simultaneous fitting across multiple datasets produces superior non-linear parameter estimates compared to sequential fitting.
Both the simultaneous equation method and the Taylor's theorem expansion effectively optimize multi-parameter non-linear models.

Cite This Study

Nimmo et al. (1976) studied this question.

synapsesocial.com/papers/6a87aca38ca276dbde792e53 https://doi.org/10.1042/bj1570489

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August 1, 1976Biochemical JournalOpen Access

Methods for fitting equations with two or more non-linear parameters

View Full Paper

Ask AI

Bookmark

Authors

INI.A. NimmoEdinburgh Royal Infirmary GAGordon L. AtkinsLouisiana State University

Discussion

Member takes

Implication

Computational analysis demonstrates improved parameter accuracy across experimental datasets, suggesting simultaneous equation fitting outperforms sequential estimation.

Key Points

To evaluate mathematical approaches for fitting equations with two or more non-linear parameters to experimental data using least-squares criteria.
Assessed two mathematical fitting procedures: directly solving a system of non-linear simultaneous equations and applying Taylor's theorem.
Compared fitting non-linear equations to all experimental datasets simultaneously against fitting datasets sequentially one by one.
Simultaneous fitting across multiple datasets produces superior non-linear parameter estimates compared to sequential fitting.
Both the simultaneous equation method and the Taylor's theorem expansion effectively optimize multi-parameter non-linear models.

Cite This Study

Nimmo et al. (1976) studied this question.

synapsesocial.com/papers/6a87aca38ca276dbde792e53 https://doi.org/10.1042/bj1570489

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