Interpreting Cubic Spline Coefficients for spline(theta, R)

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The discussion revolves around the use of spline fitting in MATLAB, specifically the output of the spline function when applied to two equal-sized arrays, theta and R. The user is confused about the interpretation of the coefficients produced by the spline function, initially expecting them to represent a polynomial in standard form. However, upon testing with original values, this assumption proved incorrect. Additionally, there is an inquiry about how to apply spline concepts to solve differential equations, indicating a desire to understand the broader applications of spline fitting beyond simple interpolation. The conversation highlights the need for clarity on spline coefficients and their mathematical implications in practical applications.
danago
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>> spline(theta, R)

ans =

form: 'pp'
breaks: [0.5000 1]
coefs: [-1.9538 1.1125 0.8415]
pieces: 1
order: 3
dim: 1

theta and R are of equal size and contain the points i want to fit to a spline.

What really has me perplexed is the coefficients that are produced. How do i interpret these coefficients; I originally assumed that they were the coefficients of a polynomial in standard form, however after plugging in my original values to check i have found that this is clearly not the case.

Any help? :smile:

Thanks in advance.
Dan.
 
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I need to know how could we solve differential equation using concept of splines
 
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