Simpson's Method for Computing Relative Error of x

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To compute x within a 0.1% relative error using Simpson's method, the integration should be performed with two different step sizes, h and h/2. By comparing the results from these two calculations, the relative difference can provide an error estimate. The provided m-files include a function for approximating the integral of f(x) over a specified interval using the composite Simpson rule. Implementing this error-checking method will enhance the accuracy of the results. This approach ensures that the desired precision in the computation of x is achieved effectively.
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I want to compute x within 0.1% relative error with Simpson method, these are my m-files. Which command i should add for this?

Matlab:
function simps(a, b, n)
%simps(a, b, n) approximates the integral of a function f(x) in the
%interval [a;b] by the composite simpson rule
%n is the number of subintervals

h = (b-a)/n;

sum_even = 0;

for i = 1:n/2-1
x(i) = a + 2*i*h;
sum_even = sum_even + f(x(i));
end

sum_odd = 0;

for i = 1:n/2
x(i) = a + (2*i-1)*h;
sum_odd = sum_odd + f(x(i));
end

integral = h*(f(a)+ 2*sum_even + 4*sum_odd +f(b))/3function y = f(x)
y=1/x;
 
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The best way to get an error estimate is to do the integration with two different values of the step (say h and h/2) and use the relative difference between the two results.
 

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