LogNormalMuSigmaOverMu¶
- class LogNormalMuSigmaOverMu(*args)¶
LogNormal distribution parameters.
- Parameters:
- mufloat
Mean .
Default value is .
- deltafloat
Variation coefficient .
Default value is .
- gammafloat, optional
Location parameter.
Default value is 0.0.
See also
Notes
Let be a random variable that follows a LogNormal distribution such that:
The native parameters of are and , which are such that follows a normal distribution whose mean is and whose variance is . Then we have:
The default values of are defined so that the associated native parameters have the default values: .
Examples
Create the parameters of the LogNormal distribution:
>>> import openturns as ot >>> parameters = ot.LogNormalMuSigmaOverMu(0.63, 5.24, -0.5)
Convert parameters into the native parameters:
>>> print(parameters.evaluate()) [-1.00525,1.50164,-0.5]
The gradient of the transformation of the native parameters into the new parameters:
>>> print(parameters.gradient()) [[ 0.256272 0.418663 0 ] [ -0.170824 0.113758 0 ] [ -1.6771 0.527516 1 ]]
Methods
evaluate
()Compute native parameters values.
Accessor to the object's name.
Get the description of the parameters.
Build a distribution based on a set of native parameters.
getName
()Accessor to the object's name.
Accessor to the parameters values.
gradient
()Get the gradient.
hasName
()Test if the object is named.
inverse
(inP)Convert to native parameters.
setName
(name)Accessor to the object's name.
setValues
(values)Accessor to the parameters values.
- __init__(*args)¶
- getClassName()¶
Accessor to the object’s name.
- Returns:
- class_namestr
The object class name (object.__class__.__name__).
- getDescription()¶
Get the description of the parameters.
- Returns:
- collection
Description
List of parameters names.
- collection
- getDistribution()¶
Build a distribution based on a set of native parameters.
- Returns:
- distribution
Distribution
Distribution built with the native parameters.
- distribution
- getName()¶
Accessor to the object’s name.
- Returns:
- namestr
The name of the object.
- gradient()¶
Get the gradient.
- Returns:
- gradient
Matrix
The gradient of the transformation of the native parameters into the new parameters.
- gradient
Notes
If we note the native parameters and the new ones, then the gradient matrix is .
- hasName()¶
Test if the object is named.
- Returns:
- hasNamebool
True if the name is not empty.
- inverse(inP)¶
Convert to native parameters.
- Parameters:
- inPsequence of float
The non-native parameters.
- Returns:
- outP
Point
The native parameters.
- outP
- setName(name)¶
Accessor to the object’s name.
- Parameters:
- namestr
The name of the object.
- setValues(values)¶
Accessor to the parameters values.
- Parameters:
- valuessequence of float
List of parameters values.