Hello,

I am working with the attached dataset, where the first column represents temperature and the next six columns (2–7) correspond to temperature-dependent properties.

I would like to explore whether it is possible to model temperature as a function of these six properties simultaneously, similar to a multiple regression approach. I have previously done this with linear responses, but in this case, the relationships are nonlinear (sigmoidal, Z-shaped).
I considered using a generalized additive model (GAM), but I have no prior experience with this method and may be overlooking a simpler or more suitable approach.

Could anyone provide insights or suggestions on how to best tackle this?
Thanks in advance! :)Hello,

I am working with the attached dataset, where the first column represents temperature and the next six columns (2–7) correspond to temperature-dependent properties.

I would like to explore whether it is possible to model temperature as a function of these six properties simultaneously, similar to a multiple regression approach. I have previously done this with linear responses, but in this case, the relationships are nonlinear (sigmoidal, Z-shaped).
I considered using a generalized additive model (GAM), but I have no prior experience with this method and may be overlooking a simpler or more suitable approach.

Could anyone provide insights or suggestions on how to best tackle this?
Thanks in advance! 🙂 Hello,

I am working with the attached dataset, where the first column represents temperature and the next six columns (2–7) correspond to temperature-dependent properties.

I would like to explore whether it is possible to model temperature as a function of these six properties simultaneously, similar to a multiple regression approach. I have previously done this with linear responses, but in this case, the relationships are nonlinear (sigmoidal, Z-shaped).
I considered using a generalized additive model (GAM), but I have no prior experience with this method and may be overlooking a simpler or more suitable approach.

Could anyone provide insights or suggestions on how to best tackle this?
Thanks in advance! 🙂 multiple regression, nonlinear, additive models, multiple variables MATLAB Answers — New Questions

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