hit_miss: Monte-Carlo integration using the hit and miss method

In david850803/MC.makes.perfect: Monte Carlo integration

Description

Monte-Carlo integration using the hit and miss method

Usage

hit_miss(ftn, a, b, f.min, f.max, n)

Arguments

ftn	a function of single variable.
a	lower bound of the integration. Must be finite.
b	upper bound of the integration. Must be finite and assume b > a.
f.min	lower bound of the ftn over the range [a,b].
f.max	upper bound of the ftn over the range [a,b].
n	number of samples used in the estimation.

References

Owen Jones,Robert Maillardet,Andrew Robinson (2014).Introduction to Scientific Programming and Simulation Using R ; Second Edition

See Also

integrate

Examples

## We see that the number of repetitions n needs to be very large
## in order to get even just two decimal places of accuracy.
f <- function(x) return(x^3 - 7 * x^2 + 1 )
hit_miss(f, 0, 1, -6, 2, 1000)
hit_miss(f, 0, 1, -6, 2, 10000)
hit_miss(f, 0, 1, -6, 2, 100000)
hit_miss(f, 0, 1, -6, 2, 1000000)

david850803/MC.makes.perfect documentation built on June 16, 2019, 12:04 a.m.