Simulating Dice Rolls in R

Question

I am trying to code the following game in R:

• Roll a dice until you observe a 4 followed by a 6
• Count how many times it took you to observe a 4 followed by a 6
• Repeat these first two steps 100 times
• Calculate the average number of times it took to observe a 4 followed by a 6

I tried to manually simulate this as follows - I first used the "runif" command in R to "roll a dice" a large number of times, hoping that you will eventually see a 4 followed by a 6 (I don't know how to code this using "do until loops"). I repeated this 100 times and put all these rolls into a data frame:

roll_1 = floor(runif(100, min=1, max=6))

roll_2 = floor(runif(100, min=1, max=6))

roll_3 = floor(runif(100, min=1, max=6))

roll_4 = floor(runif(100, min=1, max=6))

roll_5 = floor(runif(100, min=1, max=6))

#etc 

roll_100 = floor(runif(100, min=1, max=6))

all_rolls = data.frame(roll_1, roll_2, roll_3, roll_4, roll_5, roll_100)

This looks as follows:

head(all_rolls)
  roll_1 roll_2 roll_3 roll_4 roll_5 roll_100
1      4      2      5      3      1        4
2      3      2      4      4      1        2
3      1      3      1      4      2        1
4      3      2      1      4      4        3
5      4      1      2      2      5        5
6      2      3      3      5      3        1

I then exported this data frame into Microsoft Excel and manually inspected each column and counted the row number at which a 6 appears when preceded by a 4. I then averaged this number for all columns and calculated the average number of times you need to roll a dice before you observe a 4 followed by a 6. This took some time to do, but it worked.

I am looking for a quicker way to do this. Does anyone know if "do until" loops can be used in R to accelerate this "game"?

Thanks

Answer 1

Instead of runif, I would sample 1:6 value since a die would have only values from 1 to 6 and will not have values like 1.23 etc.

This is how you can use while loop -

roll_from_4_to6 <- function() {
  n <- 1:6
  i <- 1
  previous_4 <- FALSE
  while(TRUE) {
    current_value = sample(n, 1)
    i <- i + 1
    if(previous_4 && current_value == 6) break
    previous_4 <- current_value == 4
  }
  i
}

Run it once.

roll_from_4_to6()

Run it 100 times and take the average.

mean(replicate(100, roll_from_4_to6()))