Generating random variables from normal distribution
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I generated random variables from a normal distribution. I used this: normrnd(mu, sigma, N, 1). Mu = 0.146053128 and sigma = 0.13470517. The problem is some of the random numbers generated are negative.
My question is: 1. How do I generate all positive (non-negative) random numbers from normal distribution? 2. Can someone kindly explain why the negative numbers were generated since I have no idea and cannot explain why that happened.
Please I really need help.
Thanks in advance
Ruby
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Matthew
am 25 Sep. 2012
If you just want to truncate the tail so that you don't get negative numbers, the below would work.
normArray = normrnd(mu, sigma, N, 1);
normArray(normArray<0) = 0;
3 Kommentare
Matt Fig
am 25 Sep. 2012
Except then normArray is not a normal distribution...
N = normrnd(.1, .9, 1000000, 1);
subplot(1,2,1)
hist(N,-6:.05:6) % What a normal dist looks like
N(N<0) = 0;
subplot(1,2,2)
hist(N,-6:.05:6) % Not a normal dist.
mohammed sportman
am 7 Okt. 2012
how r u math can you help me to chose random number from matrix with possible to repeat the number more than once time (possion distribution)
Image Analyst
am 8 Okt. 2012
Matthew's is not normal, but Matt's isn't exactly what was asked for either. It's still normal but the mean shifted upwards from the desired location. For another way to do it (again, not producing what was wanted, or normal), you can simply remove the negative numbers altogether:
normArray(normArray < 0) = []; % Eliminate negative numbers.
This will also reduce the number of elements in the array of course, so you might want to ask for way more than is necessary and then truncate to the number you want:
normArray(desiredNumberOfElements+1:end) = []; % Get rid of extra unneeded #'s.
or alternatively:
normArray = normArray(1:desiredNumberOfElements); % Get rid of extra unneeded #'s.
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