Higher order scrambled digital nets achieve the optimal rate of the root mean square error for smooth integrands
高阶扰乱数字网对光滑被积函数达到最优均方根误差收敛率
We study a random sampling technique to approximate integrals ∫[0, 1]s f(x) dx by averaging the function at some sampling points. We focus on cases where the integrand is smooth, which is a problem which occurs in statistics. The convergence rate of the approximation error depends on the smoothness of the function f and the sampling technique. For instance, Monte Carlo (MC) sampling yields a convergence of the root mean square error (RMSE) of order N−1/2 (where N is the…