@@StudySessionYT Hi i was also wondering, assuming my dataset tends to an asymptote at the end, how would i use cubic spline interpolation to adjust for that? I fit the data using that however, it doesn't accurately mimic asymptotic behavior. Is there anything i can do so that i can make it so? Thank you :)
If you are using MATLAB, it is just as easy as saying: syms x % and let's say you need the cubic function in the first segment y1 = a1*x^3 + b1*x^2 + c1*x + d1 In Python you can use import sympy as sym x = sym.Symbol('x') # this should work as well
Underrated! Thanks so much man!!! This is so helpful!!!
Glad you liked it! Thank you for watching!
@@StudySessionYT Hi i was also wondering, assuming my dataset tends to an asymptote at the end, how would i use cubic spline interpolation to adjust for that? I fit the data using that however, it doesn't accurately mimic asymptotic behavior. Is there anything i can do so that i can make it so?
Thank you :)
This helped so much.... Best video I have seen by a mile and will be sharing with all my classmates
Bro this is crystal clear. Thank you so much for help
Don't you need to substitute (x-1) , (x-3),(x-5)... to x in those polynomials?
Incredible vidéo, thank you very much !!!
beautiful! thank you
Thanks for watching!
Is it possible to get access to the python code?
unbelievably goated
how to find the natural Cubic Spline Interpolation in parametric form?
If you are using MATLAB, it is just as easy as saying:
syms x
% and let's say you need the cubic function in the first segment
y1 = a1*x^3 + b1*x^2 + c1*x + d1
In Python you can use
import sympy as sym
x = sym.Symbol('x')
# this should work as well
Can somebody explain, how to calculate a,b,c and d?
It is just a linear system of equation. This video may help: studio.th-cam.com/users/videoEjFptcxgw28/edit