Another method to calculate integrals is using approximate numerical methods, which you may see somewhere in Calculus, such as Riemann Sums. Newton-Cotes formulas are a class of methods to achieve that purpose. These include popular rules like Simpson’s rule, midpoint rule, Trapezoidal rule, …
Euclidean Division
Given 2 polynomials and , there exist 2 polynomial (quotient) and (remainder) which statisfy
and
Polynomial Remainder Theorem
Given number and polynomial , by using Euclidean Division theorem for and
Then replacing , we get
which is the remainder. Thus we can rewrite the formula as
Chinese Remainder Theorem
Given pairwise coprime positive numbers and integers such that with then
has a solution.
Bézout’s Identity
Let and be integers and is the greatest common divisor of and . Then there exists and such that
Solution
Let so thus by Bézout’s identity we have
then the solution of the system is
Lagrange Interpolation
Rewrite the system for polynomial we have
thus the solution of is
where and
Polynomial Interpolation
Interpolating polynomial is defined to be a polynomial that fits a set of given data points of a function and give the exact value corresponding the value of the function being approximated.
Lagrange Interpolation
Let be the Lagrange Polynomial order of that passes through set of data points and is defined as
where is the Lagrange basis polynomial.
Let then the basis can be also represented as
Newton Interpolation
Instead of using Lagrange Polynomial, you can use Newton Polynomial form which is defined as
or by the recursive relation
where is divided difference and with is the Newton basis polynomial.
The forward divided differences can be defined as
It can be also represented by using Newton tableau
By putting the point we get
where
This is also called the remainder of the interpolation polynomial.
Hermite Interpolation Formula
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Let be the closed contour that contains except the point then from and we have
Now by extending the contour to which contains the points and
or
which is also the remainder term of lagrange polynomial.
So the contour integral representation on contour for lagrange polynomial can be written as
or
This is also known as Hermite interpolation formula
Approximation Error
Consisder remainder term which is the approximation error when approximating function with Interpolation Polynomial
Because the Interpolation Polynomial itself gives the exact value of point thus
Contour integral form of the remainder
Lagrange form of the remainder
Newton form of the remainder
Thus we can observe that has at least distinct zeros at . By Rolle’s theorem between distict and , there exists at least one of . Thus, has at least zeros between and . So on, we can conclude that has at least one zero in the interval
Now by the newton interpolation, we know that Hence, we obtain the mean value theorem for Divided Differences
Finally we can rewrite the remainder as
where
Newton–Cotes Formulas
After constructing the Lagrance polynomial, Newton–Cotes formulas can be defined as follows
where
with for closed formula.
with for closed formula.
To be able to use we need to calculate the weights
Then can be rewritten as
Error Analysis
The error of the Newton–Cotes formulas is defined as
So using we obtain
where . Thus we obtain
substitute we get the form
For with it is known as the rectangle rule
For with and we get the trapiozal rule
For with points , , and it becomes the 1/3 Simpson’s rule
Oops zero appears!! But it doesnt mean the error is zero. It is just because the cubic term is zero. Instead, we can use the next term of the newton polynomial by adding one more interpolation point to calculate it