craps: Monte Carlo Simulation of the Dice Game "Craps"

In simEd: Simulation Education

Monte Carlo Simulation of the Dice Game "Craps"

Description

A Monte Carlo simulation of the dice game "craps". Returns a point estimate of the probability of winning craps using fair dice.

Usage

craps(nrep = 1000, seed = NA, showProgress = TRUE)

Arguments

nrep	Number of replications (plays of a single game of craps)
seed	Initial seed to the random number generator (NA uses current state of random number generator; NULL seeds using system clock)
showProgress	If TRUE, displays a progress bar on screen during execution

Details

Implements a Monte Carlo simulation of the dice game craps played with fair dice. A single play of the game proceeds as follows:

• Two fair dice are rolled. If the sum is 7 or 11, the player wins immediately; if the sum is 2, 3, or 12, the player loses immediately. Otherwise the sum becomes the point.

• The two dice continue to be rolled until either a sum of 7 is rolled (in which case the player loses) or a sum equal to the point is rolled (in which case the player wins).

The simulation involves nrep replications of the game.

Note: When the value of nrep is large, the function will execute noticeably faster when showProgress is set to FALSE.

Value

Point estimate of the probability of winning at craps (a real-valued scalar).

Author(s)

Barry Lawson ([e-mail]),
Larry Leemis ([e-mail]),
Vadim Kudlay ([e-mail])

See Also

base::set.seed

Examples

 # set the initial seed externally using set.seed;
 # then use that current state of the generator with default nrep = 1000
 set.seed(8675309)
 craps()  # uses state of generator set above

 # explicitly set the seed in the call to the function,
 # using default nrep = 1000
 craps(seed = 8675309)

 # use the current state of the random number generator with nrep = 10000
 prob <- craps(10000)

 # explicitly set nrep = 10000 and seed = 8675309
 prob <- craps(10000, 8675309)

simEd documentation built on Nov. 27, 2023, 1:07 a.m.