Triangular CDF VI
- Updated2025-07-30
- 3 minute(s) read
Computes the continuous cumulative distribution function (CDF), or the probability that the random variate X, where X describes the selected distribution type, has a value less than or equal to x. You must manually select the polymorphic instance to use.

Inputs/Outputs
x
—
x specifies the quantile of the continuous random variate and is bounded by the interval [xmin, xmax].
xmin
—
xmin specifies the lower limit parameter of the variate.
xmode
—
xmode specifies the mode parameter of the variate. The default is NaN, which corresponds to a mode at the midpoint between xmin and xmax.
xmax
—
xmax specifies the upper limit parameter of the variate.
cdf(x)
—
cdf(x) returns the cumulative probability that the random variate X, where X describes the selected distribution type, has a value less than or equal to x.
error
—
error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster. |
When you use the Beta CDF instance of this VI, X represents a beta-distributed variate, which is restricted to a finite interval [0, 1], with given shape parameters a and b.
The CDF function with a beta distribution also is known as the beta cumulative distribution function (CDF), the beta distribution function, or the incomplete beta function.
Examples
Refer to the following example files included with LabVIEW.
- labview\examples\Mathematics\Probability and Statistics\Display Continuous Probability Distributions.vi
x
—
cdf(x)
—
error
—