mcintegral: Monte Carlo and Quasi-Monte Carlo integration in any...

In obreschkow/cooltools: Practical Tools for Scientific Computations and Visualizations

Monte Carlo and Quasi-Monte Carlo integration in any dimension

Description

Numerical integration using a Monte Carlo (MC) or Quasi-Monte Carlo (QMC) algorithm, based on a Halton sequence. These algorithms are of low order (1/sqrt(n) for MC, log(n)/n for QMC in one dimension) compared to the typical orders of 1D deterministic integrators, such as those available in the integrate function. The MC and QMC integrators are suitable to compute D-dimensional integrals with D>>1, since the order of most deterministic methods deteriorates exponentially with D, whereas the order of MC remains 1/sqrt(n), irrespective of D, and the order of QMC only deteriorates slowly with D as log(n)^D/n.

Usage

mcintegral(f, a, b, n = 1e+05, qmc = FALSE, seed = NULL, warn = TRUE)

Arguments

f	scalar function of a D-vector to be integrated numerically; for fast performance, this function should be vectorized, such that it returns an N-element vector if it is given an N-by-D matrix as argument. An automatic warning is produced if the function is not vectorized in this manner.
a	D-vector with lower limit(s) of the integration
b	D-vector with upper limit(s) of the integration
n	approximate number of random evaluations. (The exact number is max(1,round(sqrt(n)))^2.)
qmc	logical flag. If false (default), pseudo-random numbers are used; if true, quasi-random numbers from a D-dimensional Halton sequence are used.
seed	optional seed for random number generator. Only used if qmc is false.
warn	logical flag. If true (default), a warning is produced if the function f is not vectorized.

Value

Returns a list of items:

value	the best estimate of the integral.
error	an estimate of the statistical 1-sigma uncertainty.
iterations	exact number of evaluations (close to n).

Author(s)

Danail Obreschkow

Examples

## Numerically integrate sin(x)
f = function(x) sin(x)
m = mcintegral(f,0,pi)
cat(sprintf('Integral = %.3f\u00B1%.3f (true value = 2)\n',m$value,m$sigma))

## Numerically compute the volume of a unit sphere
sphere = function(x) as.numeric(rowSums(x^2)<=1) # this is vectorized
vmc = mcintegral(sphere,rep(-1,3),rep(1,3),seed=1)
vqmc = mcintegral(sphere,rep(-1,3),rep(1,3),qmc=TRUE)
cat(sprintf('Volume of unit sphere = %.3f\u00B1%.3f (MC)\n',vmc$value,vmc$error))
cat(sprintf('Volume of unit sphere = %.3f\u00B1%.3f (QMC)\n',vqmc$value,vqmc$error))
cat(sprintf('Volume of unit sphere = %.3f (exact)\n',4*pi/3))

obreschkow/cooltools documentation built on Nov. 16, 2024, 2:46 a.m.