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Distfun >> Distfun > Uniform > distfun_unifrnd

distfun_unifrnd

Uniform random numbers

Calling Sequence

R = distfun_unifrnd ( a , b )
R = distfun_unifrnd ( a , b , [m,n] )
R = distfun_unifrnd ( a , b , m , n )

Parameters

a :

a matrix of doubles, the lower bound

b :

a matrix of doubles, the upper bound (with a<=b)

m :

a 1-by-1 matrix of floating point integers, the number of rows of R

n :

a 1-by-1 matrix of floating point integers, the number of columns of R

R:

a matrix of doubles, the random numbers in the interval [a,b].

Description

Generates random variablesfrom the Uniform distribution function.

Any scalar input argument is expanded to a matrix of doubles of the same size as the other input arguments.

Examples

// Set the seed so as to always get the same results.
distfun_seedset(1);

// Use R = distfun_unifrnd ( a , b )
distfun_unifrnd(1:6,2:7)
distfun_unifrnd(1:6,7)
distfun_unifrnd(1,2:7)

// Check mean and variance for R = distfun_unifrnd ( a , b )
N = 1000;
a = 1:6;
b = 2:7;
m = (a+b)/2; // Expectation
v = (b-a).^2/12.; // Variance
for i = 1:N
computed(i,1:6) = distfun_unifrnd(a,b);
end
c = mean(computed(1:N,1:6) , "r" )
disp(m)
c = st_deviation(computed(1:N,1:6) , "r" )
e = sqrt(v)

// Check R = distfun_unifrnd ( a , b , v )
computed = distfun_unifrnd(2,3,[1 5])
computed = distfun_unifrnd(2,3,[3 2])

// Check mean and variance for R = distfun_unifrnd ( a , b )
N = 1000;
a = 2;
b = 3;
m = (a+b)/2; // Expectation
v = (b-a).^2/12.; // Variance
computed = distfun_unifrnd(2,3,[1 N]);
c = mean(computed(1:N) )
disp(m)
c = st_deviation(computed(1:N) )
e = sqrt(v)

// Check R = distfun_unifrnd ( a , b , m , n )
computed = distfun_unifrnd([1 2 3;4 5 6],7,2,3)
computed = distfun_unifrnd(4,5,2,3)
computed = distfun_unifrnd(0,[1 2 3;4 5 6],2,3)

// Check mean and variance for R = distfun_unifrnd ( a , b )
N = 1000;
a = 2;
b = 3;
m = a .* b; // Expectation
v = m .* b; // Variance
computed = distfun_unifrnd(a,b,1,N);
c = mean(computed(1:N) )
disp(m)
c = st_deviation(computed(1:N) )
e = sqrt(v)

// Make a plot of the actual distribution of the numbers
a = 2;
b = 3;
data = distfun_unifrnd(a,b,1,1000);
scf();
histplot(10,data)
x = linspace(a-1,b+1,1000);
y = distfun_unifpdf(x,a,b);
plot(x,y)
xtitle("Uniform random numbers","X","Density");
legend(["Empirical","PDF"]);

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