SG++
python.uq.dists.Corr.Corr Class Reference
Inheritance diagram for python.uq.dists.Corr.Corr:

Public Member Functions

def __init__ (self, dists)
 
def __str__ (self)
 
def fromJson (cls, jsonObject)
 
def getBounds (self)
 
def getDim (self)
 
def getDistributions (self)
 
def pdf (self, x)
 
def rvs (self, n=1)
 
def toJson (self)
 

Detailed Description

Models the multivariate distribution of correlated

Constructor & Destructor Documentation

def python.uq.dists.Corr.Corr.__init__ (   self,
  dists 
)

References python.uq.dists.Corr.Corr.__dim, python.uq.analysis.asgc.anova.hdmrAnalytic.HDMRAnalytic.__dim, python.learner.LearnerBuilder.LearnerBuilder.GridDescriptor.__dim, and python.uq.dists.Corr.Corr.__dists.

Member Function Documentation

def python.uq.dists.Corr.Corr.__str__ (   self)

References python.uq.dists.Corr.Corr.__dists.

def python.uq.dists.Corr.Corr.fromJson (   cls,
  jsonObject 
)
Restores the Corr object from the json object with its
attributes.
@param jsonObject: json object
@return: the restored Corr object

Referenced by python.uq.sampler.asgc.ASGCSampler.ASGCSampler.setMemento(), python.uq.learner.Learner.Learner.setMemento(), and python.uq.uq_setting.UQSetting.UQSetting.setMemento().

def python.uq.dists.Corr.Corr.getBounds (   self)

References python.uq.dists.Corr.Corr.__dists.

Referenced by python.uq.dists.Dist.Dist.l2error().

def python.uq.dists.Corr.Corr.getDim (   self)

References python.uq.dists.Corr.Corr.__dim, python.uq.analysis.asgc.anova.hdmrAnalytic.HDMRAnalytic.__dim, and python.learner.LearnerBuilder.LearnerBuilder.GridDescriptor.__dim.

Referenced by python.uq.dists.Dist.Dist.cov(), python.uq.parameters.ParameterSet.ParameterSet.extractActiveSubset(), and python.uq.uq_setting.UQSetting.UQSetting.getDim().

def python.uq.dists.Corr.Corr.getDistributions (   self)

References python.uq.dists.Corr.Corr.__dists.

Referenced by python.uq.parameters.ParameterSet.ParameterSet.getIndependentJointDistribution().

def python.uq.dists.Corr.Corr.pdf (   self,
  x 
)
When x is correlated to y, but y not to x then the joint
probability density is defined as

p(x, y) = p(x|y) * p(y)

The correlation is described as a tuple (x, (y, )).

References python.uq.dists.Corr.Corr.__dim, python.uq.analysis.asgc.anova.hdmrAnalytic.HDMRAnalytic.__dim, python.learner.LearnerBuilder.LearnerBuilder.GridDescriptor.__dim, and python.uq.dists.Corr.Corr.__dists.

Referenced by python.uq.dists.Dist.Dist.crossEntropy(), python.uq.dists.Dist.Dist.klDivergence(), and python.uq.dists.Dist.Dist.l2error().

def python.uq.dists.Corr.Corr.rvs (   self,
  n = 1 
)

References python.uq.dists.Corr.Corr.__dists.


The documentation for this class was generated from the following file: