dice: Simulate rolling dice

Description

Simulate and optionally plot rolls of dice.

Usage

dice(rolls = 1, ndice = 2, sides = 6, plot.it = FALSE, load = rep(1, sides))
# S3 method for dice
plot(x, ...)

Arguments

rolls

Scalar, the number of times to roll the dice.

ndice

Scalar, the number of dice to roll each time.

sides

Scalar, the number of sides per die.

plot.it

Logical, Should the results be plotted.

load

Vector of length sides, how the dice should be loaded.

Data frame, return value from dice.

…

Additional arguments passed to lattice plotting function.

Value

A data frame with rolls rows and ndice columns representing the results from rolling the dice.

If only 1 die is rolled, then the return value will be a vector.

If plot.it is TRUE, then the return value will be invisible.

Details

Simulates the rolling of dice. By default it will roll 2 dice 1 time and the dice will be fair. Internally the sample function is used and the load option is passed to sample. load is not required to sum to 1, but the elements will be divided by the sum of all the values.

Examples

Run this code

# NOT RUN {
# 10 rolls of 4 fair dice
dice(10,4, plot.it=TRUE)

# or

plot(dice(10,4))

# or

tmp <- dice(10,4)
plot(tmp)

# a loaded die
table(tmp <- dice(100,1,plot.it=TRUE, load=6:1 ) )
colMeans(tmp)

# Efron's dice
ed <- list( rep( c(4,0), c(4,2) ),
  rep(3,6), rep( c(6,2), c(2,4) ),
  rep( c(5,1), c(3,3) ) )

tmp <- dice( 10000, ndice=4 )
ed.out <- sapply(1:4, function(i) ed[[i]][ tmp[[i]] ] )

mean(ed.out[,1] > ed.out[,2])
mean(ed.out[,2] > ed.out[,3])
mean(ed.out[,3] > ed.out[,4])
mean(ed.out[,4] > ed.out[,1])


## redo De Mere's question

demere1 <- dice(10000,4)
demere2 <- dice(10000,24,sides=36)

mean(apply( demere1, 1, function(x) 6 %in% x ))

mean(apply( demere2, 1, function(x) 36 %in% x))

plot(demere1[1:10,])

## plot all possible combinations of 2 dice

plot.dice( expand.grid(1:6,1:6), layout=c(6,6) )
# }