File List

Here is a list of all files with brief descriptions:

[detail level 1234]

doxygen
txt_common
about_vpath.page
acknowledgment.page
lgpl.page
noop.page
queso.page
src
basic
inc
ArrayOfSequences.h
BoxSubset.h
ConcatenationSubset.h
ConstantScalarFunction.h
ConstantVectorFunction.h
DiscreteSubset.h
GenericScalarFunction.h
GenericVectorFunction.h
InstantiateIntersection.h	A templated method to calculate intersection of two domains (vector spaces)
IntersectionSubset.h
ScalarFunction.h	Set of classes for handling vector functions
ScalarFunctionSynchronizer.h	Class for synchronizing the calls of scalar functions
ScalarSequence.h	A templated class for handling scalar samples
SequenceOfVectors.h
SequenceStatisticalOptions.h
VectorFunction.h
VectorFunctionSynchronizer.h	Class for synchronizing the calls of vector-valued functions
VectorSequence.h	A templated class for handling vector and arrays samples
VectorSet.h
VectorSpace.h
VectorSubset.h
src
ArrayOfSequences.C
BoxSubset.C
ConcatenationSubset.C
ConstantScalarFunction.C
ConstantVectorFunction.C
DiscreteSubset.C
GenericScalarFunction.C
GenericVectorFunction.C
GslVectorSpace.C
InstantiateIntersection.C
IntersectionSubset.C
ScalarFunction.C
ScalarFunctionSynchronizer.C
ScalarSequence.C
SequenceOfVectors.C
SequenceStatisticalOptions.C
TeuchosVectorSpace.C
VectorFunction.C
VectorFunctionSynchronizer.C
VectorSequence.C
VectorSet.C
VectorSpace.C
VectorSubset.C
core
inc
asserts.h
BasicPdfsBase.h	Class for Basic PDFs
BasicPdfsBoost.h	Class for Basic PDFs using Boost library
BasicPdfsGsl.h	Class for Basic PDFs using Gsl library
Defines.h	Definitions and a class to provide default options to pass to a QUESO environment
DistArray.h	A class to store row-oriented multi-vectors of type T
Environment.h	Class to set up a QUESO environment
EnvironmentOptions.h	Class to allow options to be passed to a QUESO environment
exceptions.h
FunctionBase.h	Abstract base class for function objects
FunctionOperatorBuilder.h	Helper class for function and operator objects. This class is meant to hold common FEM library backend options in a library-agnostic fashion
GslBlockMatrix.h	QUESO block matrix class using GSL
GslMatrix.h	QUESO matrix class using GSL
GslOptimizer.h	Class for handling optimization of scalar functions
GslVector.h	Vector class using GSL
InfiniteDimensionalGaussian.h	Class defining infinite dimensional Gaussian measures
InfiniteDimensionalLikelihoodBase.h	Abstract class representing the likelihood
InfiniteDimensionalMCMCSampler.h
InfiniteDimensionalMCMCSamplerOptions.h	This class defines the options that specify the behaviour of the MCMC sampler
InfiniteDimensionalMeasureBase.h	Abstract base class for infinite dimensional measures
LibMeshFunction.h
LibMeshNegativeLaplacianOperator.h
LibMeshOperatorBase.h
Map.h	A class for partitioning vectors and matrices
Matrix.h	Matrix class
MpiComm.h	MPI Communicator Class
OperatorBase.h	Abstract base class for operator objects
Optimizer.h	Class for handling optimization of scalar functions
OptimizerMonitor.h
queso.h
RngBase.h	Random Number Generation class
RngBoost.h	Boost Random Number Generation class
RngGsl.h	GSL Random Number Generation class
TeuchosMatrix.h
TeuchosVector.h
Vector.h	Vector class
src
BasicPdfsBase.C
BasicPdfsBoost.C
BasicPdfsGsl.C
Defines.C
DistArray.C
Environment.C
EnvironmentOptions.C
FunctionBase.C
FunctionOperatorBuilder.C
GslBlockMatrix.C
GslMatrix.C
GslOptimizer.C
GslVector.C
InfiniteDimensionalGaussian.C
InfiniteDimensionalLikelihoodBase.C
InfiniteDimensionalMCMCSampler.C
InfiniteDimensionalMCMCSamplerOptions.C
InfiniteDimensionalMeasureBase.C
LibMeshFunction.C
LibMeshNegativeLaplacianOperator.C
LibMeshOperatorBase.C
Map.C
Matrix.C
MpiComm.C
OperatorBase.C
Optimizer.C
OptimizerMonitor.C
RngBase.C
RngBoost.C
RngGsl.C
TeuchosMatrix.C
TeuchosVector.C
Vector.C
version.C
misc
inc
1D1DFunction.h
1DQuadrature.h
2dArrayOfStuff.h
ArrayOfOneDGrids.h	Class to accommodate arrays of one-dimensional grid
ArrayOfOneDTables.h
AsciiTable.h	Class to read ASCII values from a table
CovCond.h
Fft.h	Matrix class
Miscellaneous.h
OneDGrid.h	Classes to accommodate a one dimensional grid
StdOneDGrid.h
UniformOneDGrid.h
src
1D1DFunction.C
1DQuadrature.C
2dArrayOfStuff.C
ArrayOfOneDGrids.C
ArrayOfOneDTables.C
AsciiTable.C
ComplexFft.C
CovCond.C
Fft.C
GslAsciiTable.C
Miscellaneous.C
OneDGrid.C
RealFft.C
StdOneDGrid.C
UniformOneDGrid.C
stats
inc
BayesianJointPdf.h
BetaJointPdf.h
BetaVectorRealizer.h
BetaVectorRV.h
ConcatenatedJointPdf.h
ConcatenatedVectorRealizer.h
ConcatenatedVectorRV.h
ExponentialMatrixCovarianceFunction.h
ExponentialScalarCovarianceFunction.h
FiniteDistribution.h
GammaJointPdf.h
GammaVectorRealizer.h
GammaVectorRV.h
GaussianJointPdf.h
GaussianLikelihood.h
GaussianLikelihoodBlockDiagonalCovariance.h
GaussianLikelihoodBlockDiagonalCovarianceRandomCoefficients.h
GaussianLikelihoodDiagonalCovariance.h
GaussianLikelihoodFullCovariance.h
GaussianLikelihoodFullCovarianceRandomCoefficient.h
GaussianLikelihoodScalarCovariance.h
GaussianVectorCdf.h
GaussianVectorMdf.h
GaussianVectorRealizer.h
GaussianVectorRV.h
GenericJointPdf.h
GenericMatrixCovarianceFunction.h
GenericScalarCovarianceFunction.h
GenericVectorCdf.h
GenericVectorMdf.h
GenericVectorRealizer.h
GenericVectorRV.h
HessianCovMatricesTKGroup.h
InfoTheory.h
InverseGammaJointPdf.h
InverseGammaVectorRealizer.h
InverseGammaVectorRV.h
InvLogitGaussianJointPdf.h
InvLogitGaussianVectorRealizer.h
InvLogitGaussianVectorRV.h
JeffreysJointPdf.h
JeffreysVectorRealizer.h
JeffreysVectorRV.h
JointPdf.h	Classes to accommodate a probability density
LogNormalJointPdf.h
LogNormalVectorRealizer.h
LogNormalVectorRV.h
MarkovChainPositionData.h	A templated class that represents a Markov Chain
MatrixCovarianceFunction.h	Classes to accommodate covariance matrix of random vector functions
MetropolisHastingsSG.h	A templated class that represents a Metropolis-Hastings generator of samples and a struct which stores its info
MetropolisHastingsSGOptions.h	Classes to allow options to be passed to a Metropolis-Hastings algorithm
MLSampling.h
MLSamplingLevelOptions.h	Classes to allow options to be passed to the Multilevel algorithm, per level
MLSamplingOptions.h	Classes to allow options to be passed to the Multilevel algorithm
ModelValidation.h	A templated class for model validation of the example validationPyramid
MonteCarloSG.h	A templated class that implements a Monte Carlo generator of samples
MonteCarloSGOptions.h
PoweredJointPdf.h
SampledScalarCdf.h
SampledVectorCdf.h
SampledVectorMdf.h
ScalarCdf.h	Classes to accommodate a cumulative distribution function
ScalarCovarianceFunction.h	Classes to accommodate covariance of scalar functions (random variables)
ScalarGaussianRandomField.h	A class for handling Gaussian random fields (GRF)
ScaledCovMatrixTKGroup.h
SequentialVectorRealizer.h
StatisticalForwardProblem.h	Class to solve a Statistical Forward Problem
StatisticalForwardProblemOptions.h
StatisticalInverseProblem.h	Class to solve a Statistical Inverse Problem
StatisticalInverseProblemOptions.h	Classes to allow options to be passed to a Statistical Inverse Problem
StdScalarCdf.h
TKGroup.h	Class to set up a Transition Kernel
TransformedScaledCovMatrixTKGroup.h
UniformJointPdf.h
UniformVectorRealizer.h
UniformVectorRV.h
ValidationCycle.h	A templated class for validation cycle of the examples validationCycle and validationCycle2
VectorCdf.h	Classes to accommodate a cumulative distribution function of a vector RV
VectorGaussianRandomField.h	A class for handling Gaussian random fields (GRF)
VectorMdf.h	Classes to accommodate a marginal density function of a vector RV
VectorRealizer.h	A templated class for sampling from vector RVs (holding probability density distributions)
VectorRV.h	A templated class for handling vector random variables (RV)
WignerJointPdf.h
WignerVectorRealizer.h
WignerVectorRV.h
src
BayesianJointPdf.C
BetaJointPdf.C
BetaVectorRealizer.C
BetaVectorRV.C
ConcatenatedJointPdf.C
ConcatenatedVectorRealizer.C
ConcatenatedVectorRV.C
ExponentialMatrixCovarianceFunction.C
ExponentialScalarCovarianceFunction.C
FiniteDistribution.C
GammaJointPdf.C
GammaVectorRealizer.C
GammaVectorRV.C
GaussianJointPdf.C
GaussianLikelihood.C
GaussianLikelihoodBlockDiagonalCovariance.C
GaussianLikelihoodBlockDiagonalCovarianceRandomCoefficients.C
GaussianLikelihoodDiagonalCovariance.C
GaussianLikelihoodFullCovariance.C
GaussianLikelihoodFullCovarianceRandomCoefficient.C
GaussianLikelihoodScalarCovariance.C
GaussianVectorCdf.C
GaussianVectorMdf.C
GaussianVectorRealizer.C
GaussianVectorRV.C
GenericJointPdf.C
GenericMatrixCovarianceFunction.C
GenericScalarCovarianceFunction.C
GenericVectorCdf.C
GenericVectorMdf.C
GenericVectorRealizer.C
GenericVectorRV.C
HessianCovMatricesTKGroup.C
InfoTheory.C
InverseGammaJointPdf.C
InverseGammaVectorRealizer.C
InverseGammaVectorRV.C
InvLogitGaussianJointPdf.C
InvLogitGaussianVectorRealizer.C
InvLogitGaussianVectorRV.C
JeffreysJointPdf.C
JeffreysVectorRealizer.C
JeffreysVectorRV.C
JointPdf.C
LogNormalJointPdf.C
LogNormalVectorRealizer.C
LogNormalVectorRV.C
MarkovChainPositionData.C
MatrixCovarianceFunction.C
MetropolisHastingsSG.C
MetropolisHastingsSGOptions.C
MLSampling.C
MLSamplingLevelOptions.C
MLSamplingOptions.C
ModelValidation.C
MonteCarloSG.C
MonteCarloSGOptions.C
PoweredJointPdf.C
SampledScalarCdf.C
SampledVectorCdf.C
SampledVectorMdf.C
ScalarCdf.C
ScalarCovarianceFunction.C
ScalarGaussianRandomField.C
ScaledCovMatrixTKGroup.C
SequentialVectorRealizer.C
StatisticalForwardProblem.C
StatisticalForwardProblemOptions.C
StatisticalInverseProblem.C
StatisticalInverseProblemOptions.C
StdScalarCdf.C
TKGroup.C
TransformedScaledCovMatrixTKGroup.C
UniformJointPdf.C
UniformVectorRealizer.C
UniformVectorRV.C
ValidationCycle.C
VectorCdf.C
VectorGaussianRandomField.C
VectorMdf.C
VectorRealizer.C
VectorRV.C
WignerJointPdf.C
WignerVectorRealizer.C
WignerVectorRV.C