Chapter 11: Probability Distribution Functions and Inverses

HYPPR

This function evaluates the hypergeometric probability density function.

Function Return Value

HYPPR — Function value, the probability that a hypergeometric random variable takes a value equal to K.   (Output)
HYPPR is the probability that exactly K defectives occur in a sample of size N drawn from a lot of size L that contains M defectives.
See Comment 1.

Required Arguments

K — Argument for which the hypergeometric probability function is to be evaluated.   (Input)

N — Sample size.   (Input)
N must be greater than zero and greater than or equal to K.

M — Number of defectives in the lot.   (Input)

L — Lot size.   (Input)
L must be greater than or equal to N and M.

FORTRAN 90 Interface

Generic:                              HYPPR (K, N, M, L)

Specific:                             The specific interface names are S_HYPPR and D_HYPPR.

FORTRAN 77 Interface

Single:                                HYPPR (K, N, M, L)

Double:                              The double precision name is DHYPPR.

Description

The function HYPPR evaluates the probability density function of a hypergeometric random variable with parameters n, l, and m. The hypergeometric random variable X can be thought of as the number of items of a given type in a random sample of size n that is drawn without replacement from a population of size l containing m items of this type. The probability density function is

 

where i = max(0, nl + m). HYPPR evaluates the expression using log gamma functions.

Comments

1.         If the generic version of this function is used, the immediate result must be stored in a variable before use in an expression. For example:

X = HYPPR(K, N, M, L)

Y = SQRT(X)

            must be used rather than

Y = SQRT(HYPPR(K, N, M, L))

            If this is too much of a restriction on the programmer, then the specific name can be used without this restriction.

2.         Informational errors

Type Code

1         5                  The input argument, K, is less than zero.

1         6                  The input argument, K, is greater than the sample size.

Example

Suppose X is a hypergeometric random variable with N = 100, L = 1000, and M = 70. In this example, we evaluate the probability function at 7.

 

      USE UMACH_INT

      USE HYPPR_INT

 

      IMPLICIT   NONE

      INTEGER    K, L, M, N, NOUT

      REAL       PR

!

      CALL UMACH (2, NOUT)

      K  = 7

      N  = 100

      L  = 1000

      M  = 70

      PR = HYPPR(K,N,M,L)

      WRITE (NOUT,99999) PR

99999 FORMAT (' The probability that X is equal to 7 is ', F6.4)

      END

Output

 

The probability that X is equal to 7 is 0.1628



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