Beta random numbers
x = distfun_betarnd ( a , b ) x = distfun_betarnd ( a , b , [m,n] ) x = distfun_betarnd ( a , b , m , n )
a matrix of doubles, the first shape parameter, a>=0.
a matrix of doubles, the first shape parameter, b>=0.
a 1-by-1 matrix of floating point integers, the number of rows of x
a 1-by-1 matrix of floating point integers, the number of columns of x
a matrix of doubles, the random numbers, in the interval [0,1].
Generates random variables from the Beta distribution.
Any scalar input argument is expanded to a matrix of doubles of the same size as the other input arguments.
// Use x = distfun_betarnd ( a , b ) x=distfun_betarnd(1:6,(1:6)^-1) x=distfun_betarnd(1:6,1) x=distfun_betarnd(1,(1:6)^-1) // Check x = distfun_betarnd ( a , b , v ) x = distfun_betarnd(2,1,[1 5]) x = distfun_betarnd(2,1,[3 2]) // Use x = distfun_betarnd ( a , b , m , n ) x = distfun_betarnd([1 2 3;4 5 6],0.1,2,3) x = distfun_betarnd(2,1,2,3) x = distfun_betarnd(1,[1 2 3;4 5 6],2,3) // Check mean and variance for x = distfun_betarnd ( a , b ) N = 1000; a = 1:6; b = (1:6)^-1; for i = 1:N computed(i,1:6) = distfun_betarnd(a,b); end [M,V] = distfun_betastat ( a , b ) Mx = mean(computed, "r") Vx = variance(computed, "r") // Make a plot of the actual distribution of the numbers a = 2; b = 3; x = distfun_betarnd(a,b,1,1000); histplot(10,x) x = linspace(0,1,1000); y = distfun_betapdf(x,a,b); plot(x,y) xtitle("Beta random variables","X","Density"); legend(["Empirical","PDF"]); | ![]() | ![]() |