The IMSL_HYPERGEOCDF function evaluates the hypergeometric distribution function.

This routine requires an IDL Advanced Math and Stats license. For more information, contact your sales or technical support representative.

The IMSL_HYPERGEOCDF function evaluates the distribution 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 function is:

where i = max(0, n – l + m).

If k is greater than or equal to i and less than or equal to min(n, m), IMSL_BINOMIALCDF sums the terms in this expression for j going from i up to k; otherwise, 0 or 1 is returned, as appropriate. To avoid rounding in the accumulation, IMSL_BINOMIALCDF performs the summation differently, depending on whether or not k is greater than the mode of the distribution, which is the greatest integer in (m + 1) (n + 1)/(l + 2).

Example


Suppose X is a hypergeometric random variable with n = 100, l = 1000, and m = 70. In this example, the distribution function is evaluated at 7.

p = IMSL_HYPERGEOCDF(7, 100, 70, 1000)
PM, 'Pr(x <= 7) = ', p, FORMAT = '(a13,f7.4)'

IDL prints:

Pr(x <= 7) = 0.5995

Syntax


Result = IMSL_HYPERGEOCDF(K, N, M, L [, /DOUBLE])

Return Value


The probability that K or fewer defectives occur in a sample of size N drawn from a lot of size L that contains M defectives.

Arguments


K

Parameter for which the hypergeometric distribution function is to be evaluated.

L

Lot size. Parameter L must be greater than or equal to N and M.

M

Number of defectives in the lot.

N

Sample size. Argument n must be greater than or equal to k.

Keywords


DOUBLE (optional)

If present and nonzero, double precision is used.

Errors


Informational Errors

STAT_LESS_THAN_ZERO: Input parameter, k, is less than zero.

STAT_K_GREATER_THAN_N: Input parameter, k, is greater than the sample size.

Fatal Errors

STAT_LOT_SIZE_TOO_SMALL: Lot size must be greater than or equal to n and m.

Version History


6.4

Introduced