Normal

Normal distribution

Description

The normal (or Gaussian) distribution object defines a normal distribution function with the provided mean and standard_deviation parameters. The probability density function (PDF) of the normal distribution is given by the Eq. (1).

(1)

where is the mean and is the standard deviation () of the distribution.

This implementation of a normal distribution uses a numerical approximation described in Kennedy and Gentle (2018).

Example Input Syntax

The following input file defines a normal distribution with a mean of 0 and a standard deviation of 1.

[Distributions]
  [normal_test]
    type = Normal
    mean = 0
    standard_deviation = 1
  []
[]
(contrib/moose/modules/stochastic_tools/test/tests/distributions/normal.i)

Input Parameters

  • meanMean (or expectation) of the distribution.

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Mean (or expectation) of the distribution.

  • standard_deviationStandard deviation of the distribution

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Standard deviation of the distribution

Required Parameters

  • control_tagsAdds user-defined labels for accessing object parameters via control logic.

    C++ Type:std::vector<std::string>

    Unit:(no unit assumed)

    Controllable:No

    Description:Adds user-defined labels for accessing object parameters via control logic.

  • enableTrueSet the enabled status of the MooseObject.

    Default:True

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:Set the enabled status of the MooseObject.

Advanced Parameters

References

  1. William J Kennedy and James E Gentle. Statistical computing. Routledge, 2018.[BibTeX]