python.uq.estimators.CollocationPointsStrategy.CollocationPointsStrategy Class Reference

Inheritance diagram for python.uq.estimators.CollocationPointsStrategy.CollocationPointsStrategy:

Public Member Functions
def	mean (self, grid, alpha, U, T)
def	var (self, grid, alpha, U, T, mean)

Member Function Documentation

mean()

def python.uq.estimators.CollocationPointsStrategy.CollocationPointsStrategy.mean	(		self,
			grid,
			alpha,
			U,
			T
	)

Estimate the expectation value using

\frac{1}{N}\sum\limits_{i = 1}^N f_N(x_i) pdf(x_i)

where x_i are the sparse grid collocation points

References python.uq.estimators.SparseGridEstimationStrategy.SparseGridEstimationStrategy._extractPDFforMomentEstimation(), and python.uq.operations.sparse_grid.dehierarchize().

Referenced by python.uq.analysis.mc.MCAnalysis.MCAnalysis.computeMoments(), and python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.computeMoments().

var()

def python.uq.estimators.CollocationPointsStrategy.CollocationPointsStrategy.var	(		self,
			grid,
			alpha,
			U,
			T,
			mean
	)

Estimate the expectation value using

\frac{1}{N}\sum\limits_{i = 1}^N (f_N(x_i) - E(f))^2 pdf(x_i)

where x_i are the sparse grid collocation points

References python.uq.estimators.SparseGridEstimationStrategy.SparseGridEstimationStrategy._extractPDFforMomentEstimation(), and python.uq.operations.sparse_grid.dehierarchize().

Referenced by python.uq.analysis.mc.MCAnalysis.MCAnalysis.computeMoments(), and python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.computeMoments().

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

• datadriven/python/uq/estimators/CollocationPointsStrategy.py