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Discrete uniform inverse cumulative distribution function


X = unidinv(P,N)


X = unidinv(P,N) returns the smallest positive integer X such that the discrete uniform cdf evaluated at X is equal to or exceeds P. You can think of P as the probability of drawing a number as large as X out of a hat with the numbers 1 through N inside.

P and N can be vectors, matrices, or multidimensional arrays that have the same size, which is also the size of X. A scalar input for N or P is expanded to a constant array with the same dimensions as the other input. The values in P must lie on the interval [0 1] and the values in N must be positive integers.


x = unidinv(0.7,20)
x =

y = unidinv(0.7 + eps,20)
y =

A small change in the first parameter produces a large jump in output. The cdf and its inverse are both step functions. The example shows what happens at a step.

Introduced before R2006a

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