Package Modelica.​Math.​Distributions.​Interfaces
Library of interfaces for distribution functions

Information

This package contains partial functions that describe the common interface arguments of the distribution and truncated distribution functions.

Extends from Modelica.​Icons.​InterfacesPackage (Icon for packages containing interfaces).

Package Contents

NameDescription
partialCumulativeCommon interface of cumulative distribution functions
partialDensityCommon interface of probability density functions
partialQuantileCommon interface of quantile functions (= inverse cumulative distribution functions)
partialTruncatedCumulativeCommon interface of truncated cumulative distribution functions
partialTruncatedDensityCommon interface of truncated probability density functions
partialTruncatedQuantileCommon interface of truncated quantile functions (= inverse cumulative distribution functions)

Partial Function Modelica.​Math.​Distributions.​Interfaces.​partialDensity
Common interface of probability density functions

Information

A partial function containing the common arguments of the probability density functions.

Extends from Modelica.​Icons.​Function (Icon for functions).

Inputs

TypeNameDescription
RealuRandom number over the real axis (-inf < u < inf)

Outputs

TypeNameDescription
RealyDensity of u

Partial Function Modelica.​Math.​Distributions.​Interfaces.​partialCumulative
Common interface of cumulative distribution functions

Information

A partial function containing the common arguments of the cumulative distribution functions.

Extends from Modelica.​Icons.​Function (Icon for functions).

Inputs

TypeNameDescription
RealuValue over the real axis (-inf < u < inf)

Outputs

TypeNameDescription
RealyValue in the range 0 <= y <= 1

Partial Function Modelica.​Math.​Distributions.​Interfaces.​partialQuantile
Common interface of quantile functions (= inverse cumulative distribution functions)

Information

A partial function containing the common arguments of the quantile functions.

Extends from Modelica.​Icons.​Function (Icon for functions).

Inputs

TypeNameDescription
RealuRandom number in the range 0 <= u <= 1

Outputs

TypeNameDescription
RealyRandom number u transformed according to the given distribution

Partial Function Modelica.​Math.​Distributions.​Interfaces.​partialTruncatedDensity
Common interface of truncated probability density functions

Information

A partial function containing the common arguments of the probability density functions of truncated distributions.

Extends from Modelica.​Math.​Distributions.​Interfaces.​partialDensity (Common interface of probability density functions).

Inputs

TypeNameDescription
RealuRandom number over the real axis (-inf < u < inf)
Realu_minLower limit of u
Realu_maxUpper limit of u

Outputs

TypeNameDescription
RealyDensity of u

Partial Function Modelica.​Math.​Distributions.​Interfaces.​partialTruncatedCumulative
Common interface of truncated cumulative distribution functions

Information

A partial function containing the common arguments of the cumulative distribution functions for a truncated distribution.

Extends from Modelica.​Math.​Distributions.​Interfaces.​partialCumulative (Common interface of cumulative distribution functions).

Inputs

TypeNameDescription
RealuValue over the real axis (-inf < u < inf)
Realu_minLower limit of u
Realu_maxUpper limit of u

Outputs

TypeNameDescription
RealyValue in the range 0 <= y <= 1

Partial Function Modelica.​Math.​Distributions.​Interfaces.​partialTruncatedQuantile
Common interface of truncated quantile functions (= inverse cumulative distribution functions)

Information

A partial function containing the common arguments of the quantile functions for truncated distributions.

Extends from Modelica.​Math.​Distributions.​Interfaces.​partialQuantile (Common interface of quantile functions (= inverse cumulative distribution functions)).

Inputs

TypeNameDescription
RealuRandom number in the range 0 <= u <= 1
Realy_minLower limit of y
Realy_maxUpper limit of y

Outputs

TypeNameDescription
RealyRandom number u transformed according to the given distribution