This tutorial describes the spline basis and smoothing techniques which are based on splines.
using Plots pyplot() Here is a simple function and noisy data. The object of this tutorial is to estimate the sinuosoidal curve given the noisy observations.
x = linspace(0, 2*pi, 100)[1:end-1] y = sin(4*x) yn = y + randn(size(y)) *.2 plot(x,y) scatter!(x,yn) To do this we will use cubic splines. The spline basis with knots at $ \xi_i $ is given by $ (x-\xi_i)^3_i $ .

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