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Thank you for seeing this post.

Various regression models are being applied to the curve estimating (actual measured ventilation rate). Comparison was made using the GLM and GAM models including polynomial regression. I use R.

enter image description here

Are there any other types of regression models that can simulate that curve well? like...bayesian? (In fact, I didn't even understand if it could be applied here)

Sincerely.

Glen_b
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gwang gon Jo
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1 Answers1

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loads of non linear methods exist, and many would give similar results, but this is a statistics question. it would fit better on cross validated. also, you have to tell: do you want to do interpolation, even extrapolation? what is your analysis for?

bayesian methods are used when you have knowledge of the phenomenon prior to data, or in some cases when you want to apply regularization or graphical models to data generation processes, I think you should better leave out bayesian statistics here.

edit:

to be short: if you want to obtain a readable formulation of the curve, and you don't have any specific mathematical model in mind, go for a polynomial fit. Other popular choices, which are better for only plotting the curve, instead of reporting it in a mathematical expression, are smoothing splines and LOESS. for further details, maybe ask a new question on stats.stackexchange.com, after studing better the alternatives.

carlo
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  • Thank you for answer. I'm not professional at statistics. I measured the ventilation volume according to the voltage efficiency and plotted it. As you can see, it's a nonlinear curve. What I'm curious about is what model will replicate that curve. If I get rid of some of them, I would like to find a model that produces curves that are as close to actual measurements as possible. – gwang gon Jo Oct 13 '19 at 13:32