This implementation takes a different approach, rather than simply relying on probability, this method keeps track of the unique values found until all conditions are satisfied.
To achieve this, an empty vector called foundset is initialized, and an iteration variable iteration is set to 0. Inside the while loop, the iteration variable is incremented, and a new number is chosen using the sample() function. This function selects a random value from a specified range (in this case, 1 to 5) and assigns it to the pick variable.
Next, the code checks if the pick value is already in the foundset vector. If it's not, it means a unique value has been selected, so it's added to the foundset vector. This process continues until the length of the foundset vector reaches 5, indicating that all unique values have been found.
#initialize values
foundset <- vector()
iteration <-0
while (length(foundset) < 5) {
#increament iteration
iteration <- iteration +1
#pick a new number
pick <- sample(1:5, 1)
#see if pick in the set if not add it
if (!(pick %in% foundset)) {
foundset <- c(foundset, pick)
}
#exit if all five values are found
}
print(iteration)
print(foundset)
Finally, the iteration and foundset vectors are printed, displaying the number of iterations required to find all unique values and the set of unique values themselves.
This method provides a more deterministic approach to finding unique values within a specified range, ensuring that all conditions are met before exiting the loop.
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