# Numerical Analysis/Differentiation/Examples

When deriving a finite difference approximation of the th derivative of a function , we wish to find and such that

or, equivalently,

where is the error, the difference between the correct answer and the approximation, expressed using Big-O notation. Because may be presumed to be small, a larger value for is better than a smaller value.

A general method for finding the coefficients is to generate the Taylor expansion of and choose and such that and the remainder term are the only non-zero terms. If there are no such coefficients, a smaller value for must be chosen.

For a function of variables , the procedure is similar, except are replaced by points in and the multivariate extension of Taylor's theorem is used.

## Single-Variable[edit | edit source]

In all single-variable examples, and are unknown, and is small. Additionally, let be 5 times continuously differentiable on .

### First Derivative[edit | edit source]

Find such that best approximates .

First, we find the Taylor series expansion of with remainder term to be

If we can find a solution to the system

then we can substitute that solution into the Taylor expansion to obtain

The system of equations has exactly one solution: , , , so

Let be 42 times continuously differentiable on . Find the largest such that

In other words, find the order of the error of the method.

The Taylor expansion of the method is

Simplifying this algebraically gives

The multiple of cannot be removed, so and by properties of Big-O notation,

### Second Derivative[edit | edit source]

Find such that best approximates .

First, we find the Taylor series expansion of , with remainder term to be

If we can find a solution to the system

then we can substitute that solution into the Taylor expansion and obtain

The system of equations has exactly one solution: , , so

## Multivariate[edit | edit source]

In all two-variable examples, and are unknown, and is small.

### Non-Mixed Derivatives[edit | edit source]

Because of the nature of partial derivatives, some of them may be calculated using single-variable methods. This is done by holding constant all but one variable to form a new function of one variable. For example if , then .

Find an approximation of

Because we are differentiating with respect to only one variable, we can hold x constant and use the result of one of the single-variable examples:

### Mixed Derivatives[edit | edit source]

Mixed derivatives may require the multivariate extension of Taylor's theorem.

Let be 42 times continuously differentiable on and let be defined as

Find the largest such that

In other words, find the order of the error of the approximation.

The first few terms of the multivariate Taylor expansion of around are

We substitute the expansion for into the approximation to obtain

Because of the careful choices of coefficients, we can simplify this to

We note that Big-O notation permits us to write the last 3 terms as . Thus,

Because the multiples of are unaffected by adding more terms to the Taylor expansion, is the greatest natural number satisfying the conditions given in the problem.

## Example Code[edit | edit source]

Implementing these methods is reasonably simple in programming languages that support higher-order functions. For example, the method from the first example may be implemented in C++ using function pointers, as follows:

```
// Returns an approximation of the derivative of f at x.
double derivative (double (*f)(double), double x, double h =0.01) {
return (f(x + h) - f(x - h)) / (2 * h);
}
```