How to generate numbers from probability mass function?

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Clarisha Nijman
Clarisha Nijman 2018년 10월 9일
답변: PARTHEEBAN R 2021년 5월 22일
Hallo,
Given a probability mass function defined as P(X=3)=0.2, P(X=7)=0.3 and P(X=10)=0.5, I want to generate randomly 30 numbers (values for X) with this probability mass function as base. But I really have no idea how and where to start.
Can somebody help me?
Thank you in advance

채택된 답변

Torsten
Torsten 2018년 10월 9일
편집: Torsten 2018년 10월 9일
n = 30;
X = zeros(n,1);
x = rand(n,1);
X(x <= 0.5) = 10;
X(x > 0.5 & x <= 0.8) = 7;
X(x > 0.8) = 3;
  댓글 수: 3
Torsten
Torsten 2018년 10월 10일
For an explanation, see
https://stats.stackexchange.com/questions/26858/how-to-generate-numbers-based-on-an-arbitrary-discrete-distribution

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추가 답변 (3개)

Bruno Luong
Bruno Luong 2018년 10월 9일
A more generic method:
p = [0.2 0.3 0.5];
v = [3 7 10];
n = 10000;
c = cumsum([0,p(:).']);
c = c/c(end); % make sur the cumulative is 1
[~,i] = histc(rand(1,n),c);
r = v(i); % map to v values
  댓글 수: 1
Clarisha Nijman
Clarisha Nijman 2018년 10월 19일
This answer works for me the best. I need this to do random column sampling (sampling some columns of a very big matrix A)

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Jeff Miller
Jeff Miller 2018년 10월 20일

With Cupid you could write:

v = [3 7 10];       % the values
p = [0.2 0.3 0.5];  % their probabilities
rv = List(v,p);     % a random variable with those values & probabilities
n = 10000;
randoms = rv.Random(n,1);  % generate n random values of the random variable
  댓글 수: 3
Jeff Miller
Jeff Miller 2018년 10월 20일
Did you download the Cupid files (see the link in my answer)? These define the List class (which handles the cumulative distribution behind the scene). Do the other Cupid demos run correctly?
Well, Cupid may be overkill for your problem, but it does have a lot of flexibility.
Clarisha Nijman
Clarisha Nijman 2018년 10월 20일
Ok, tnx Jeff, I'll check it!

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PARTHEEBAN R
PARTHEEBAN R 2021년 5월 22일
A random variable X has cdf F(x) = { 0 , if x < − 1 a(1 + x ) , if − 1 < < 1 1 , if x ≥ 1 . Find (1) the value of a, (2) P(X > 1/4 ) and P ( − 0 . 5 ≤ X ≤ 0 ) .

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