I would like to generate a sample of size 20 from the multinomial distribution with three values such as 1,2 and 3. For example, the sample can be like this sam=(1,2,2,2,2,3,1,1,1,3,3,3,2,1,2,3,…1)
the following code is working but not getting the expected result
> rmultinom(20,3,c(0.4,0.3,0.3))+1 <,1> <,2> <,3> <,4> <,5> <,6> <,7> <,8> <,9> <,10> <,11> <,12> <,13> <,14> <,15> <,16> <,17> <,18> <,19> <,20><1,> 1 1 3 2 2 1 1 2 3 2 3 2 1 2 2 3 1 2 2 2<2,> 2 1 2 1 3 2 4 2 1 2 2 1 1 2 1 2 3 2 3 3<3,> 3 4 1 3 1 3 1 2 2 2 1 3 4 2 3 1 2 2 1 1I am not expecting this matrix. Any help is appreciated?
r random numbers multinomial
Share
Improve this question
Follow
asked Dec 3 “19 at 15:38
UddinUddin
70244 silver badges1111 bronze badges
4
Add a comment |
3 Answers 3
Active Oldest Votes
3
I would like to generate a sample of size 20 from the multinomial distribution
No problem, but you should remember that each sample is a vector, e.g. if you roll three dice you can get (2,5,1), or (6,2,4), or (3,3,3) etc.You should also remember that in rmultinom(n, size, prob) “n” is the sample size, and “size” is the total number of objects that are put into K boxes (when you roll three dice, the size is 3 and K=6).
You are watching: Multinomial distribution in r
with three values such as 1,2 and 3.
See more: All At Once Airborne Toxic Event Album), The Airborne Toxic Event
No problem, but you should remember that rmultinom will return the count of each value, i.e. you could think of your three values as of row names (your three values could be “red, green, blue”, “left, middle, right”, etc.)
> rmultinom(n=20, size=3, prob=c(0.4,0.3,0.3)) <,1> <,2> <,3> <,4> <,5> <,6> <,7> <,8> <,9> <,10> <,11> <,12> <,13> <,14> <,15> <,16> <,17> <,18> <,19> <,20><1,> 2 1 1 2 1 1 3 1 1 3 2 1 0 0 0 1 3 2 2 1<2,> 1 1 1 1 0 1 0 1 2 0 1 2 2 2 1 1 0 0 1 0<3,> 0 1 1 0 2 1 0 1 0 0 0 0 1 1 2 1 0 1 0 2In the first sample (first column) “1” occurs 2 times, “2” occurs 1 time, “3” occurs 0 times. In the second and third samples each value occurs 1 time,… in the seventh sample “1” occurs 3 times etc.Since you are putting three (size=3) objects into K=3 boxes (there are as many boxes as the length of the prob vector), the sum of each column is the number of your objects.
See more: A Thousand Kisses Deep, By Leonard Cohen A Thousand Kisses Deep Poem
For example, the sample can be like this sam=(1,2,2,2,2,3,1,1,1,3,3,3,2,1,2,3,…1)
This does not look like a sample of size 20, because the outcome of a single multinomial trial is a vector, not a number.
Let”s return to dice. I roll size=3 dice:
> rmultinom(n=1, size=3, prob=rep(1/6,6)) <,1> <1,> 0<2,> 2<3,> 0<4,> 0<5,> 1<6,> 0I get two “2”s and one “5”. This is a sample of size 1. Here is a sample of size 10:
> rmultinom(n=10, size=3, prob=rep(1/6,6)) <,1> <,2> <,3> <,4> <,5> <,6> <,7> <,8> <,9> <,10><1,> 0 0 1 0 0 0 0 1 1 1<2,> 1 1 0 3 0 0 1 1 1 1<3,> 2 1 0 0 0 0 2 0 0 0<4,> 0 0 2 0 1 1 0 1 0 1<5,> 0 0 0 0 1 2 0 0 1 0<6,> 0 1 0 0 1 0 0 0 0 0HTH
