#### 7.7.10.2 Discrete Distributions ¶

The following discrete distributions are available:

Function: PDF.BERNOULLI `(x)` ¶
Function: CDF.BERNOULLI `(x, p)` ¶
Function: RV.BERNOULLI `(p)` ¶

  Bernoulli distribution with probability of success p. Constraints: x = 0 or 1, 0 <= p <= 1.

Function: PDF.BINOM `(x, n, p)` ¶
Function: CDF.BINOM `(x, n, p)` ¶
Function: RV.BINOM `(n, p)` ¶

  Binomial distribution with n trials and probability of success p. Constraints: integer n > 0, 0 <= p <= 1, integer x <= n.

Function: PDF.GEOM `(x, n, p)` ¶
Function: CDF.GEOM `(x, n, p)` ¶
Function: RV.GEOM `(n, p)` ¶

  Geometric distribution with probability of success p. Constraints: 0 <= p <= 1, integer x > 0.

Function: PDF.HYPER `(x, a, b, c)` ¶
Function: CDF.HYPER `(x, a, b, c)` ¶
Function: RV.HYPER `(a, b, c)` ¶

  Hypergeometric distribution when b objects out of a are drawn and c of the available objects are distinctive. Constraints: integer a > 0, integer b <= a, integer c <= a, integer x >= 0.

Function: PDF.LOG `(x, p)` ¶
Function: RV.LOG `(p)` ¶

  Logarithmic distribution with probability parameter p. Constraints: 0 <= p < 1, x >= 1.

Function: PDF.NEGBIN `(x, n, p)` ¶
Function: CDF.NEGBIN `(x, n, p)` ¶
Function: RV.NEGBIN `(n, p)` ¶

  Negative binomial distribution with number of successes parameter n and probability of success parameter p. Constraints: integer n >= 0, 0 < p <= 1, integer x >= 1.

Function: PDF.POISSON `(x, mu)` ¶
Function: CDF.POISSON `(x, mu)` ¶
Function: RV.POISSON `(mu)` ¶

  Poisson distribution with mean mu. Constraints: mu > 0, integer x >= 0.