Class List

Here are the classes, structs, unions and interfaces with brief descriptions:
AnalyticConditionalGaussianAbstract Class representing all _FULL_ Analytical Conditional gaussians
AnalyticConditionalGaussianAdditiveNoiseAbstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise
AnalyticMeasurementModelGaussianUncertainty
AnalyticSystemModelGaussianUncertaintyClass for analytic system models with additive Gauss. uncertainty
ASIRFilterASIR: Auxiliary Particle Filter
BackwardFilterVirtual Baseclass representing all bayesian backward filters
BootstrapFilterParticular particle filter : Proposal PDF = SystemPDF
ColumnVectorWrapper class for ColumnVectors (Boost implementation)
ColumnVector_WrapperClass ColumnVectorWrapper
ConditionalGaussianAbstract Class representing all Conditional gaussians
ConditionalGaussianAdditiveNoiseAbstract Class representing all Conditional Gaussians with additive gaussian noise
ConditionalPdfAbstract Class representing conditional Pdfs P(x | ...)
DiscreteConditionalPdfAbstract Class representing all _FULLY_ Discrete Conditional PDF's
DiscretePdfClass representing a PDF on a discrete variable
DiscreteSystemModelClass for discrete System Models
EKFProposalDensityProposal Density for non-linear systems with additive Gaussian Noise (using a EKF Filter)
EKParticleFilterParticle filter using EKF for proposal step
ExtendedKalmanFilter
FilterAbstract class representing an interface for Bayesian Filters
FilterProposalDensityProposal Density for non-linear systems with additive Gaussian Noise (using a (analytic) Filter)
GaussianClass representing Gaussian (or normal density)
HistogramFilterClass representing the histogram filter
InnovationCheckClass implementing an innovationCheck used in IEKF
IteratedExtendedKalmanFilter
KalmanFilterClass representing the family of all Kalman Filters (EKF, IEKF, ...)
LinearAnalyticConditionalGaussianLinear Conditional Gaussian
LinearAnalyticMeasurementModelGaussianUncertaintyClass for linear analytic measurementmodels with additive gaussian noise
LinearAnalyticMeasurementModelGaussianUncertainty_ImplicitClass for linear analytic measurementmodels with additive gaussian noise
LinearAnalyticSystemModelGaussianUncertaintyClass for linear analytic systemmodels with additive gaussian noise
MatrixImplementation of Matrixwrapper using Boost
Matrix_WrapperClass Matrixwrapper
MCPdfMonte Carlo Pdf: Sample based implementation of Pdf
MeasurementModel
MixtureClass representing a mixture of PDFs, the mixture can contain different
NonLinearAnalyticConditionalGaussian_GinacConditional Gaussian for an analytic nonlinear system using Ginac:
NonLinearAnalyticMeasurementModelGaussianUncertainty_GinacClass for nonlinear analytic measurementmodels with additive gaussian noise
NonLinearAnalyticSystemModelGaussianUncertainty_GinacClass for nonlinear analytic systemmodels with additive gaussian noise
NonminimalKalmanFilter
OptimalImportanceDensityOptimal importance density for Nonlinear Gaussian SS Models
OptimalimportancefilterParticular particle filter: Proposal PDF = Optimal Importance function
ParticleFilterVirtual Class representing all particle filters
ParticleSmootherClass representing a particle backward filter
PdfClass PDF: Virtual Base class representing Probability Density Functions
ProbabilityClass representing a probability (a double between 0 and 1)
RauchTungStriebelClass representing all Rauch-Tung-Striebel backward filters
RowVectorWrapper class for RowVectors (Boost implementation)
RowVector_WrapperClass RowVectorWrapper
Sample
SRIteratedExtendedKalmanFilter
SymmetricMatrix_WrapperClass SymmetricMatrixWrapper
SystemModel
UniformClass representing uniform density
WeightedSample

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