The GAUSS_PDF function computes the cumulative distribution function for a standard Gaussian (normal) distribution. This is the probability P that, in a Gaussian distribution with a mean of 0.0 and a variance of 1.0, a random variable X is less than or equal to a user-specified cutoff value V.
This routine is written in the IDL language. Its source code can be found in the file gauss_pdf.pro in the lib subdirectory of the IDL distribution.
Examples
Example 1
Compute the probability that a random variable X, from the standard Gaussian (normal) distribution, is less than or equal to 2.44:
PRINT, GAUSS_PDF(2.44)
IDL Prints:
0.992656
Example 2
Compute the probability that a random variable X, from the standard Gaussian (normal) distribution, is less than or equal to 10.0 and greater than or equal to 2.0:
PRINT, GAUSS_PDF(10.0) - GAUSS_PDF(2.0)
IDL Prints:
0.0227501
Example 3
Compute the probability that a random variable X, from the Gaussian (normal) distribution with a mean of 0.8 and a variance of 4.0, is less than or equal to 2.44:
PRINT, GAUSS_PDF( (2.44 - 0.80)/SQRT(4.0) )
IDL Prints:
0.793892
Syntax
Result = GAUSS_PDF(V)
Return Value
This function returns a scalar or array with the same dimensions as V. If V is double-precision, the result is double-precision, otherwise the result is single-precision.
Arguments
V
A scalar or array that specifies the cutoff value(s).
Keywords
None.
Version History
See Also
BINOMIAL, CHISQR_PDF, F_PDF, GAUSS_CVF, T_PDF