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My assignment says:

"Create an .m file that is a function that creates an array of N random integers in the range from -9999 to 9999. It should be in the form of x=randint(N)."

But I have no idea how to do that. I've tried everything. This is due in 4 days.

David Hill
on 16 Jan 2020

function out=randint(N)

out=randi(19999,1,N)-10000;

end

David Hill
on 16 Jan 2020

Thanks for the comment. Good reason to look at the documentation.

out=randi([-9999,9999],1,N);

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Meg Noah
on 16 Jan 2020

If the numbers are supposed to be uniformly distributed, then they are between 0 and 1. So just linearly scale the value 0 to the minimum and value 1 to the maximum. Subtract 0.5 to make it zero mean. Multiply by the range (max-min). If the result supposed to have a 0 mean (which your example does), then the offset needs to adjusted. The min after doing that will be -range*0.5. Add range*0.5 and subtract the minvalue. For example, a histogram of 1000 points between -5 and 5 is:

histogram(2*5*rand(1000)-5)

If you want a normal distribution, and you don't have the statistics toolbox, you have to write your own. This will do:

function [harvest] = getRandomGaussianDistribution(nvals)

N = ceil(nvals/2);

v1 = rand(N,1);

v2 = rand(N,1);

idx = 1:N;

while (~isempty(idx))

v1(idx) = rand(numel(idx),1);

v2(idx) = rand(numel(idx),1);

v1(idx) = 2*v1(idx) - 1;

v2(idx) = 2*v2(idx) - 1;

rsq = v1.^2 + v2.^2;

idx = find(rsq >= 1.0 | rsq <= 0);

end

rsq = sqrt(-2.0.*log(rsq)./rsq);

harvest = vertcat(v1.*rsq, v2.*rsq);

harvest = (harvest-mean(harvest)./std(harvest));

harvest = harvest(1:nvals);

end

Then you have to search and exclude outliars because of the nature of statistics. Normalization is done by subtracting the mean and dividing by the standard deviation.

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