19 May 2025

Newton Forward and Backward Interpolation

numerical-methods interpolation finite-differences newton-formulae

Suppose $y_i=f(x_i)$ is known at equally spaced points

\[x_i=x_0+ih,\qquad i=0,1,\ldots,n.\]

Newton’s forward formula is convenient near the beginning of the table; the backward formula is convenient near its end.

Difference operators

The forward differences are

\[\Delta y_i=y_{i+1}-y_i,\] \[\Delta^2y_i=\Delta y_{i+1}-\Delta y_i,\]

with higher differences defined repeatedly. The backward differences are

\[\nabla y_i=y_i-y_{i-1},\qquad \nabla^2y_i=\nabla y_i-\nabla y_{i-1}.\]

At the final tabulated point,

\[\nabla^r y_n=\Delta^r y_{n-r}.\]

Derivation of the forward formula

Let $E$ be the shift operator, $Ey_i=y_{i+1}$. Since $\Delta=E-1$,

\[E=1+\Delta.\]

Put $p=(x-x_0)/h$. Extending the shift from an integer to the interpolation variable gives

\[f(x)=E^p y_0=(1+\Delta)^p y_0.\]

The generalized binomial expansion is

\[(1+\Delta)^p =1+p\Delta+\frac{p(p-1)}{2!}\Delta^2 +\frac{p(p-1)(p-2)}{3!}\Delta^3+\cdots.\]

Therefore

\[\boxed{ f(x)=y_0+p\Delta y_0 +\frac{p(p-1)}{2!}\Delta^2y_0 +\frac{p(p-1)(p-2)}{3!}\Delta^3y_0+\cdots }.\]

When $p$ is a non-negative integer, this reduces exactly to the corresponding tabulated value because $E^p y_0=y_p$.

Derivation of the backward formula

Since $\nabla=1-E^{-1}$, one has

\[E=(1-\nabla)^{-1}.\]

With $q=(x-x_n)/h$,

\[f(x)=E^q y_n=(1-\nabla)^{-q}y_n.\]

Using the negative-binomial expansion,

\[(1-\nabla)^{-q} =1+q\nabla+\frac{q(q+1)}{2!}\nabla^2 +\frac{q(q+1)(q+2)}{3!}\nabla^3+\cdots.\]

Hence

\[\boxed{ f(x)=y_n+q\nabla y_n +\frac{q(q+1)}{2!}\nabla^2y_n +\frac{q(q+1)(q+2)}{3!}\nabla^3y_n+\cdots }.\]

For a degree-$n$ interpolating polynomial through $n+1$ points, the remainder has the form

\[R_n(x)=\frac{f^{(n+1)}(\xi)}{(n+1)!} \prod_{j=0}^{n}(x-x_j),\]

for some $\xi$ in the data interval.

Cubic table

Take

\[f(x)=x^3-2x+1\]

at $x=0,1,2,3$:

$x$ $y$ $\Delta y$ $\Delta^2y$ $\Delta^3y$
0 1 -1 6 6
1 0 5 12  
2 5 17    
3 22      

At $x=0.5$, $p=0.5$. The forward formula gives

\[f(0.5)=1+\frac12(-1) +\frac{(1/2)(-1/2)}2(6) +\frac{(1/2)(-1/2)(-3/2)}6(6) =0.125.\]

At $x=2.5$, $q=-0.5$, while

\[\nabla y_3=17,\qquad\nabla^2y_3=12,\qquad\nabla^3y_3=6.\]

The backward formula gives

\[f(2.5)=22-\frac12(17) +\frac{(-1/2)(1/2)}2(12) +\frac{(-1/2)(1/2)(3/2)}6(6) =11.625.\]

The Maxima worksheet expands both finite-difference polynomials and displays

forward_residual  = 0
backward_residual = 0

Thus both formulae reproduce the entire cubic exactly, not only the two evaluated points.

© Rajesh Kumar, SKMU · Physics Lecture Notes · rajeshphy.github.io

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