Hi All,
Currently i manually analyse the data and generate splines (all done manually). I am trying to write a python code which can eventually run on the company server.
python's cubicspline function does not match the spline i normally generate in jmp (Analyze --> Fit Y vs X--> Flexible --> Fit spline --> Other --> Specify smoothness =0.1 check Standardize x (red)
When i am generating in Python (cubicsplines from scipy), i am getting more close to the red curve shown in the diagram.
I could not find the lambda (or equivalent) parameter in python's cubic spline function, and neither to standardize the data. i did try to standardize
(x_i-Mean(x))/Std dev (x)) the data by my own, but the curves were getting more weird.
Can some help point to what is the exact methodology/calculation used to generate these splines when we standardize the data. I have seen some post that point this is cubic splines, but i have not explanation how data is treated and spline generate when we use the standardized option.
A little far fetched, and not sure if this is the right forum, does someone know the another alternate python function that can generate matched splines?
Thank you!