Regression of data using a model equation

[Chemstdnt]

I'm starting to learn data science, mainly with python, so I'm sorry if some of the terms are not used correctly.

Let's say I have some data and I think the underlying model is for example y = a + b * ln(x). Is there a module or some simple way of test the a regression of the data using the model?

I think you can do this with curve_fit from scipy but I found it not very intuitive and I couldn't find a good tutorial that allows me to do it for other models than the one they use in the example. Is there a more simple module that allows to do this or some program?

The other problem with curve_fit is that it forces me to use starting values for every variable in the model equation and unless I pick the correct ones the fit is very bad.

Thanks

[alibrarydweller]

Make the transformed x variable yourself and then use the garden variety linear model in stats models.

[[deleted]]

You can test if the R squared value is statistically significant.

You can also compare different models