For example I have a vector about possibility is
myprob <- (0.58, 0.51, 0.48, 0.46, 0.62)
And I want to sampling a series of number between 1 and 0 each time by the probability of c(1-myprob, myprob)
,
which means in the first number in the series, the function sample 1 and 0 by (0.42, 0.58), the second by (0.49, 0.50) and so on,
how can I generate the 5 numbers by sample?
The syntax of
Y <- sample(c(1,0), 1, replace=F, prob=c(1-myprob, prob))
would have incorrect number of probabilities and only 1 number output if I specify the prob;
while the syntax of
Y <- sample(c(1,0), 5, replace=F, prob=c(1-myprob, prob))
would have the probabilities focus on only 0.62(or not I am not sure, but the results seems not correct at all)
Thanks for any reply in advance!
CodePudding user response:
If myprob
is the probability of drawing 1 for each iteration, then you can use rbinom
, with n = 5
and size = 1
(5 iterations of a 1-0 draw).
set.seed(2)
rbinom(n = 5, size = 1, prob = myprob)
[1] 1 0 1 0 0
CodePudding user response:
Maël already proposed a great solution sampling from a binomial distribution. There are probably many more alternatives and I just wanted to suggest two of them:
runif()
as.integer(runif(5) > myprob)
This will first generate a series of 5 uniformly distributed random numbers between 0 and 1, then compare that vector against myprob
and convert the logical values TRUE
/FALSE
to 1/0.
vapply(sample())
vapply(myprob, function(p) sample(1:0, 1, prob = c(1-p, p)), integer(1))
This is what you may have been looking for in the first place. This executes the sample()
command by iterating over the values of myprob
as p
and returns the 5 draws as a vector.