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Last Modified: January 12, 2018

Computes the continuous extreme value cumulative distribution function (CDF), the probability that an extreme value variate takes on a value less than or equal to the quantile of the random variable.

An extreme value distribution is the distribution of the largest extreme of a number of values.

Quantile of the continuous random variable.

**Default: **0

Location parameter of the random variable.

**Default: **0

Scale parameter of the random variable.

This input must be greater than 0.

**Default: **1

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an **error in** input and an **error out** output so that the node can respond to and communicate errors that occur while code is running. The value of **error in** specifies whether an error occurred before the node runs. Most nodes respond to values of **error in** in a standard, predictable way.

**Default: **No error

Cumulative probability that the continuous random variable has a value less than or equal to **x**.

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

**error in** input and an **error out** output so that the node can respond to and communicate errors that occur while code is running. The value of **error in** specifies whether an error occurred before the node runs. Most nodes respond to values of **error in** in a standard, predictable way.

The following equation defines the continuous CDF of an extreme value variate.

$pdf\left(x\right)=\left(\frac{1}{b}\right)\mathrm{exp}[-\frac{(x-a)}{b}]*\mathrm{exp}\{-\mathrm{exp}[-\frac{(x-a)}{b}]\}$

where

*x*is the quantile of the continuous random variable*a*is the location parameter of the random variable*b*is the scale parameter of the random variable

**Where This Node Can Run: **

Desktop OS: Windows

FPGA: Not supported

Web Server: Not supported in VIs that run in a web application