Discrete uniform cumulative distribution function

`p = unidcdf(x,N)`

p = unidcdf(x,N,'upper')

`p = unidcdf(x,N)`

returns
the discrete uniform cdf at each value in `x`

using
the corresponding maximum observable value in `N`

. `x`

and `N`

can
be vectors, matrices, or multidimensional arrays that have the same
size. A scalar input is expanded to a constant array with the same
dimensions as the other inputs. The maximum observable values in `N`

must
be positive integers.

`p = unidcdf(x,N,'upper')`

returns the complement
of the discrete uniform cdf at each value in `x`

,
using an algorithm that more accurately computes the extreme upper
tail probabilities.

The discrete uniform cdf is

$$p=F(x|N)=\frac{floor\left(x\right)}{N}{I}_{(1,\mathrm{...},N)}(x)$$

The result, *p*, is the probability that a
single observation from the discrete uniform distribution with maximum *N* will
be a positive integer less than or equal to *x*.
The values *x* do not need to be integers.

Was this topic helpful?