Simulate rolling dice
Simulate and optionally plot rolls of dice.
dice(rolls = 1, ndice = 2, sides = 6, plot.it = FALSE, load = rep(1, sides)) ## S3 method for class 'dice' plot(x, ...)
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 |
x |
Data frame, return value from |
... |
Additional arguments passed to lattice plotting function. |
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.
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.
If the plot function is used or if plot.it is TRUE, then a
plot will be created on the current graphics device.
Greg Snow 538280@gmail.com
# 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) )
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.