Re: Difference between normal_rnd (m,v, n,n) and randn (n)

[Quentin Spencer]

Henry F. Mollet wrote:

> I have to check what exactly people say when they say that they use a
> triangular distribution. I surmise that the probability density function in
> the range [0,1] increases linearly from some value at 0 to a maximum at an
> intermediate value (might be in the middle of the range) and then decreases
> linearly to some value at 1.  I'll try to modify what you gave below to get
> something that looks like a triangle. Thanks.
> Henry
>  
OK, this kind of distribution can be generated from the summation of two 
uniform random variables. Since the summation of two random variables 
has a pdf that is the convolution of the pdfs of the two variables, the 
convolution of uniform [0,1] with itself is f(x) = {x,  0<x<1 ; 2-x,  
1<x<2 ; 0 otherwise }, which is the triangular function you describe, 
centered at 1 rather than 1/2. To test this, try:

x = rand(2,N);
hist(sum(x));

You could multiply the result by a scale factor of 0.5 if you wanted the 
values in the range [0,1], for example.

Hope this helps.

-Quentin



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